{"as_of":"2026-08-22T21:41:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:ef6892642b602a8ef7d80c355d30b84e3dddc7e0fa8705c5a5690d38e98e2bda","coverage":[{"denominator":104,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":100,"source":"paper_references, paper_reference_links","source_observed_at":"2026-05-13T14:22:16.968028Z","state":"measured"},{"denominator":195,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":195,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-22T06:32:14.747728+00:00","state":"measured"},{"denominator":95,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":95,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-16T12:19:28.106999Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":1,"source":"pith","source_observed_at":"2026-08-05T02:28:24.338817Z","state":"measured"}],"external_citation_measurements":[{"count":1037,"observed_at":"2026-08-05T02:28:24.338817Z","source":"pith"}],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"cited_work":{"arxiv_id":"2210.08402","doi":"10.48550/arxiv.2210.08402","metadata_source":"pith","pith_arxiv_id":"2210.08402","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","venue":"cs.CV","work_id":"1d19deb4-3043-409d-b901-f047c51a323b","year":2022},"citing_paper":{"arxiv_id":"2302.12192","last_updated":"2023-02-23T17:34:53Z","snapshot_observed_at":"2026-08-20T08:43:12.373190Z","submitted_at":"2023-02-23T17:34:53Z","title":"Aligning Text-to-Image Models using Human Feedback","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-05-14T20:39:15.388881Z"},"links":{"cited_paper":"/paper/2210.08402","citing_paper":"/paper/2302.12192"},"observation_digest":"sha256:1f8a34189eddf96439cb9d624eb39ceff8f3d0d2280c188bb8e90d1b875b8081","observation_id":"093435d4-302f-4a37-abff-8c4252c97d3c","resolution":{"observed_at":"2026-05-14T20:39:15.547203Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"cited_work":{"arxiv_id":"2210.08402","doi":"10.48550/arxiv.2210.08402","metadata_source":"pith","pith_arxiv_id":"2210.08402","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","venue":"cs.CV","work_id":"1d19deb4-3043-409d-b901-f047c51a323b","year":2022},"citing_paper":{"arxiv_id":"2302.14045","last_updated":"2023-03-01T11:04:51Z","snapshot_observed_at":"2026-08-21T21:14:46.636998Z","submitted_at":"2023-02-27T18:55:27Z","title":"Language Is Not All You Need: Aligning Perception with Language Models","version":2},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-05-15T18:32:22.813668Z"},"links":{"cited_paper":"/paper/2210.08402","citing_paper":"/paper/2302.14045"},"observation_digest":"sha256:3bd6c07d3062a7e9200442dc8e60b9d9dc21d9d5da32af8782c4daa1e4415202","observation_id":"2133b62a-3b9a-47ad-a9a9-d54352df29ae","resolution":{"observed_at":"2026-05-15T18:32:22.975249Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"cited_work":{"arxiv_id":"2210.08402","doi":"10.48550/arxiv.2210.08402","metadata_source":"pith","pith_arxiv_id":"2210.08402","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","venue":"cs.CV","work_id":"1d19deb4-3043-409d-b901-f047c51a323b","year":2022},"citing_paper":{"arxiv_id":"2303.00915","last_updated":"2025-01-08T22:58:51Z","snapshot_observed_at":"2026-08-18T14:56:57.492279Z","submitted_at":"2023-03-02T02:20:04Z","title":"BiomedCLIP: a multimodal biomedical foundation model pretrained from fifteen million scientific image-text pairs","version":3},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-05-13T10:42:22.378367Z"},"links":{"cited_paper":"/paper/2210.08402","citing_paper":"/paper/2303.00915"},"observation_digest":"sha256:32799a6e6f4e56a2e7d17ff1dd4a7cea9a6c4bed1f85cd031de421b44f711e8a","observation_id":"3363a72c-a205-4613-bb5e-c6dd96003a1b","resolution":{"observed_at":"2026-05-13T14:22:17.864689Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"cited_work":{"arxiv_id":"2210.08402","doi":"10.48550/arxiv.2210.08402","metadata_source":"pith","pith_arxiv_id":"2210.08402","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","venue":"cs.CV","work_id":"1d19deb4-3043-409d-b901-f047c51a323b","year":2022},"citing_paper":{"arxiv_id":"2303.09540","last_updated":"2023-03-22T17:22:35Z","snapshot_observed_at":"2026-08-06T15:07:40.203199Z","submitted_at":"2023-03-16T17:53:24Z","title":"SemDeDup: Data-efficient learning at web-scale through semantic deduplication","version":3},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-05-18T02:43:30.851915Z"},"links":{"cited_paper":"/paper/2210.08402","citing_paper":"/paper/2303.09540"},"observation_digest":"sha256:54ff222dcc1a1ed40cead0ef9b5cb4fb05d261cf43a6bb64753b18b31daf80b1","observation_id":"f05fd2a2-c021-45a3-ba80-f642ef162a4b","resolution":{"observed_at":"2026-05-18T02:43:31.016105Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"cited_work":{"arxiv_id":"2210.08402","doi":"10.48550/arxiv.2210.08402","metadata_source":"pith","pith_arxiv_id":"2210.08402","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","venue":"cs.CV","work_id":"1d19deb4-3043-409d-b901-f047c51a323b","year":2022},"citing_paper":{"arxiv_id":"2303.15343","last_updated":"2023-09-27T12:05:41Z","snapshot_observed_at":"2026-07-06T15:08:30.190912Z","submitted_at":"2023-03-27T15:53:01Z","title":"Sigmoid Loss for Language Image Pre-Training","version":4},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-05-16T13:05:36.460932Z"},"links":{"cited_paper":"/paper/2210.08402","citing_paper":"/paper/2303.15343"},"observation_digest":"sha256:5e2337eb8c1e1e34d57ccd2fd497072a4a3c0a4ae090d7181123dd40f6fbb94c","observation_id":"6eba3e5b-0fcb-4e78-89f3-4cfba4a4e489","resolution":{"observed_at":"2026-05-16T13:05:36.555638Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"cited_work":{"arxiv_id":"2210.08402","doi":"10.48550/arxiv.2210.08402","metadata_source":"pith","pith_arxiv_id":"2210.08402","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","venue":"cs.CV","work_id":"1d19deb4-3043-409d-b901-f047c51a323b","year":2022},"citing_paper":{"arxiv_id":"2303.15389","last_updated":"2023-03-27T17:02:21Z","snapshot_observed_at":"2026-08-20T09:51:02.717471Z","submitted_at":"2023-03-27T17:02:21Z","title":"EVA-CLIP: Improved Training Techniques for CLIP at Scale","version":1},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-05-13T01:54:21.943160Z"},"links":{"cited_paper":"/paper/2210.08402","citing_paper":"/paper/2303.15389"},"observation_digest":"sha256:6da6d1cb5a5a54ce8259707b4cd6ffbb5a56178b5cb87261170760a8a7d414d6","observation_id":"a5ecfb2e-8233-4f49-be7d-837cd80cfe14","resolution":{"observed_at":"2026-05-13T14:22:17.864689Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"cited_work":{"arxiv_id":"2210.08402","doi":"10.48550/arxiv.2210.08402","metadata_source":"pith","pith_arxiv_id":"2210.08402","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","venue":"cs.CV","work_id":"1d19deb4-3043-409d-b901-f047c51a323b","year":2022},"citing_paper":{"arxiv_id":"2304.08485","last_updated":"2023-12-11T17:46:14Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-04-17T17:59:25Z","title":"Visual Instruction Tuning","version":2},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-05-11T08:22:03.403362Z"},"links":{"cited_paper":"/paper/2210.08402","citing_paper":"/paper/2304.08485"},"observation_digest":"sha256:5bccf2afc2f86a9c1069d7277158c4d04a95427aa45a85a100e05ece609c25c9","observation_id":"b87ff426-994f-4e02-ab03-c64b877caa2f","resolution":{"observed_at":"2026-05-13T14:22:17.864689Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"cited_work":{"arxiv_id":"2210.08402","doi":"10.48550/arxiv.2210.08402","metadata_source":"pith","pith_arxiv_id":"2210.08402","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","venue":"cs.CV","work_id":"1d19deb4-3043-409d-b901-f047c51a323b","year":2022},"citing_paper":{"arxiv_id":"2306.09341","last_updated":"2023-09-25T08:19:23Z","snapshot_observed_at":"2026-08-14T02:46:25.655503Z","submitted_at":"2023-06-15T17:59:31Z","title":"Human Preference Score v2: A Solid Benchmark for Evaluating Human Preferences of Text-to-Image Synthesis","version":2},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-05-11T08:30:48.564596Z"},"links":{"cited_paper":"/paper/2210.08402","citing_paper":"/paper/2306.09341"},"observation_digest":"sha256:3887be8a39e9840c949a0d5b89bf867e24ae6bc0d41f0968d90f1394ddd58d35","observation_id":"3ecc8efb-ad75-4637-a819-2f49dcd289e7","resolution":{"observed_at":"2026-05-13T14:22:17.864689Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"cited_work":{"arxiv_id":"2210.08402","doi":"10.48550/arxiv.2210.08402","metadata_source":"pith","pith_arxiv_id":"2210.08402","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","venue":"cs.CV","work_id":"1d19deb4-3043-409d-b901-f047c51a323b","year":2022},"citing_paper":{"arxiv_id":"2306.14685","last_updated":"2026-04-08T13:45:26Z","snapshot_observed_at":"2026-08-13T14:25:49.051992Z","submitted_at":"2023-06-26T13:30:38Z","title":"DiffSketcher: Text Guided Vector Sketch Synthesis through Latent Diffusion Models","version":5},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-05-24T08:28:28.066130Z"},"links":{"cited_paper":"/paper/2210.08402","citing_paper":"/paper/2306.14685"},"observation_digest":"sha256:e4d74af75211afd107c7b7a94f9693e0a7c5a32bcbfa2c4dd54bc2b841330c59","observation_id":"09dd5329-1795-45e2-9a86-9d81243fb934","resolution":{"observed_at":"2026-05-24T08:29:11.197237Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"cited_work":{"arxiv_id":"2210.08402","doi":"10.48550/arxiv.2210.08402","metadata_source":"pith","pith_arxiv_id":"2210.08402","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","venue":"cs.CV","work_id":"1d19deb4-3043-409d-b901-f047c51a323b","year":2022},"citing_paper":{"arxiv_id":"2306.14824","last_updated":"2023-07-13T05:41:34Z","snapshot_observed_at":"2026-08-12T12:24:23.815073Z","submitted_at":"2023-06-26T16:32:47Z","title":"Kosmos-2: Grounding Multimodal Large Language Models to the World","version":3},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-05-12T05:19:47.907355Z"},"links":{"cited_paper":"/paper/2210.08402","citing_paper":"/paper/2306.14824"},"observation_digest":"sha256:d815632c4c09c5f89376e616c64dc416b4237a3915eae34c50ed965fa1d8fa3f","observation_id":"69087584-6d18-468a-b05d-bcee8f0416e8","resolution":{"observed_at":"2026-05-13T14:22:17.864689Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"cited_work":{"arxiv_id":"2210.08402","doi":"10.48550/arxiv.2210.08402","metadata_source":"pith","pith_arxiv_id":"2210.08402","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","venue":"cs.CV","work_id":"1d19deb4-3043-409d-b901-f047c51a323b","year":2022},"citing_paper":{"arxiv_id":"2307.04725","last_updated":"2024-02-08T18:08:57Z","snapshot_observed_at":"2026-08-17T14:04:31.230742Z","submitted_at":"2023-07-10T17:34:16Z","title":"AnimateDiff: Animate Your Personalized Text-to-Image Diffusion Models without Specific Tuning","version":2},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-05-10T22:52:19.359362Z"},"links":{"cited_paper":"/paper/2210.08402","citing_paper":"/paper/2307.04725"},"observation_digest":"sha256:5c5644ad40528f2ffc6a398c8be6812cad0f3d2eefb298fe430dbf9eed9713f9","observation_id":"6d26e7c6-04e3-43fb-93c5-c36c278a4f2c","resolution":{"observed_at":"2026-05-13T14:22:17.864689Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"cited_work":{"arxiv_id":"2210.08402","doi":"10.48550/arxiv.2210.08402","metadata_source":"pith","pith_arxiv_id":"2210.08402","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","venue":"cs.CV","work_id":"1d19deb4-3043-409d-b901-f047c51a323b","year":2022},"citing_paper":{"arxiv_id":"2307.05663","last_updated":"2023-07-11T17:57:40Z","snapshot_observed_at":"2026-08-17T00:31:15.553571Z","submitted_at":"2023-07-11T17:57:40Z","title":"Objaverse-XL: A Universe of 10M+ 3D Objects","version":1},"reference_index":55,"source":"pdf_text","source_observed_at":"2026-05-17T13:02:11.512409Z"},"links":{"cited_paper":"/paper/2210.08402","citing_paper":"/paper/2307.05663"},"observation_digest":"sha256:3ae2c6299e245416354ba0b5fe4fbc4ca0a8689abb53fe812dac56619a4ff61b","observation_id":"920f8942-4bc0-4c09-8c18-857ac6f8b838","resolution":{"observed_at":"2026-05-17T13:02:11.693503Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"cited_work":{"arxiv_id":"2210.08402","doi":"10.48550/arxiv.2210.08402","metadata_source":"pith","pith_arxiv_id":"2210.08402","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","venue":"cs.CV","work_id":"1d19deb4-3043-409d-b901-f047c51a323b","year":2022},"citing_paper":{"arxiv_id":"2307.06942","last_updated":"2024-01-04T05:00:34Z","snapshot_observed_at":"2026-07-06T15:53:46.393481Z","submitted_at":"2023-07-13T17:58:32Z","title":"InternVid: A Large-scale Video-Text Dataset for Multimodal Understanding and Generation","version":2},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-05-15T06:30:22.431538Z"},"links":{"cited_paper":"/paper/2210.08402","citing_paper":"/paper/2307.06942"},"observation_digest":"sha256:9dee51e39e0ec8cd9054113a54b34f6fd2644e3a5fa89c9ceaaa186920f6d9e7","observation_id":"fb00fe86-e1e5-4de8-baff-04656ad4b9e5","resolution":{"observed_at":"2026-05-15T06:30:22.539337Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"cited_work":{"arxiv_id":"2210.08402","doi":"10.48550/arxiv.2210.08402","metadata_source":"pith","pith_arxiv_id":"2210.08402","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","venue":"cs.CV","work_id":"1d19deb4-3043-409d-b901-f047c51a323b","year":2022},"citing_paper":{"arxiv_id":"2307.10373","last_updated":"2023-11-20T10:54:09Z","snapshot_observed_at":"2026-08-15T03:17:05.670808Z","submitted_at":"2023-07-19T18:00:03Z","title":"TokenFlow: Consistent Diffusion Features for Consistent Video Editing","version":3},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-05-17T20:17:47.001786Z"},"links":{"cited_paper":"/paper/2210.08402","citing_paper":"/paper/2307.10373"},"observation_digest":"sha256:578fe4effb298537b6ea4564326f4ff29c7b2995cd3f8430d47ee0e98c760aa2","observation_id":"c4d0985e-5758-40c8-bab6-b96478198530","resolution":{"observed_at":"2026-05-17T20:17:47.090937Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"cited_work":{"arxiv_id":"2210.08402","doi":"10.48550/arxiv.2210.08402","metadata_source":"pith","pith_arxiv_id":"2210.08402","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","venue":"cs.CV","work_id":"1d19deb4-3043-409d-b901-f047c51a323b","year":2022},"citing_paper":{"arxiv_id":"2308.01390","last_updated":"2023-08-07T17:53:09Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-08-02T19:10:23Z","title":"OpenFlamingo: An Open-Source Framework for Training Large Autoregressive Vision-Language Models","version":2},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-05-14T01:52:01.163900Z"},"links":{"cited_paper":"/paper/2210.08402","citing_paper":"/paper/2308.01390"},"observation_digest":"sha256:99ffe1848bbd836e2140b203fd46b30184f8c66db4d604061b3daa45fd70be48","observation_id":"6db3821f-a629-4b36-9039-b164190af60d","resolution":{"observed_at":"2026-05-14T01:52:01.319593Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"cited_work":{"arxiv_id":"2210.08402","doi":"10.48550/arxiv.2210.08402","metadata_source":"pith","pith_arxiv_id":"2210.08402","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","venue":"cs.CV","work_id":"1d19deb4-3043-409d-b901-f047c51a323b","year":2022},"citing_paper":{"arxiv_id":"2310.01852","last_updated":"2024-01-22T03:11:15Z","snapshot_observed_at":"2026-08-16T17:54:32.088103Z","submitted_at":"2023-10-03T07:33:27Z","title":"LanguageBind: Extending Video-Language Pretraining to N-modality by Language-based Semantic Alignment","version":7},"reference_index":148,"source":"arxiv_source","source_observed_at":"2026-05-17T03:27:58.952076Z"},"links":{"cited_paper":"/paper/2210.08402","citing_paper":"/paper/2310.01852"},"observation_digest":"sha256:7e35aa105377274993410188b25b2c745e2a75bd845533a2b9c84a45bbfdd9a1","observation_id":"8abd12e9-9c6b-41f6-912e-3bd58c807bda","resolution":{"observed_at":"2026-05-17T03:27:59.131392Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"cited_work":{"arxiv_id":"2210.08402","doi":"10.48550/arxiv.2210.08402","metadata_source":"pith","pith_arxiv_id":"2210.08402","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","venue":"cs.CV","work_id":"1d19deb4-3043-409d-b901-f047c51a323b","year":2022},"citing_paper":{"arxiv_id":"2310.04378","last_updated":"2023-10-06T17:11:58Z","snapshot_observed_at":"2026-08-20T13:49:06.053430Z","submitted_at":"2023-10-06T17:11:58Z","title":"Latent Consistency Models: Synthesizing High-Resolution Images with Few-Step Inference","version":1},"reference_index":81,"source":"arxiv_source","source_observed_at":"2026-05-13T04:15:54.681913Z"},"links":{"cited_paper":"/paper/2210.08402","citing_paper":"/paper/2310.04378"},"observation_digest":"sha256:94b50e0f19c4f4924c9683bfa18f23156437f51e565a4daf09dc4152eb0eb57c","observation_id":"cd0c019f-e78f-4ee0-b750-dc7da350cea9","resolution":{"observed_at":"2026-05-13T14:22:17.864689Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"cited_work":{"arxiv_id":"2210.08402","doi":"10.48550/arxiv.2210.08402","metadata_source":"pith","pith_arxiv_id":"2210.08402","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","venue":"cs.CV","work_id":"1d19deb4-3043-409d-b901-f047c51a323b","year":2022},"citing_paper":{"arxiv_id":"2405.09818","last_updated":"2025-03-21T05:54:00Z","snapshot_observed_at":"2026-08-12T11:54:14.007649Z","submitted_at":"2024-05-16T05:23:41Z","title":"Chameleon: Mixed-Modal Early-Fusion Foundation Models","version":2},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-05-11T10:03:27.919346Z"},"links":{"cited_paper":"/paper/2210.08402","citing_paper":"/paper/2405.09818"},"observation_digest":"sha256:15eb196b7e2d60f8232385f33ad0850e3ef9f414dfa87905e3d7b2f37ffebc8d","observation_id":"bfea16de-7b25-4e0f-be8b-e00504a24f84","resolution":{"observed_at":"2026-05-13T14:22:17.864689Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"cited_work":{"arxiv_id":"2210.08402","doi":"10.48550/arxiv.2210.08402","metadata_source":"pith","pith_arxiv_id":"2210.08402","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","venue":"cs.CV","work_id":"1d19deb4-3043-409d-b901-f047c51a323b","year":2022},"citing_paper":{"arxiv_id":"2406.02509","last_updated":"2024-06-04T17:27:19Z","snapshot_observed_at":"2026-08-21T19:57:02.214817Z","submitted_at":"2024-06-04T17:27:19Z","title":"CamCo: Camera-Controllable 3D-Consistent Image-to-Video Generation","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-05-16T19:43:33.639639Z"},"links":{"cited_paper":"/paper/2210.08402","citing_paper":"/paper/2406.02509"},"observation_digest":"sha256:14b446366e383cfa4b1c6d8c2aa5488808f0a90fdf369407242b2520a57e0ffb","observation_id":"65dc648f-8771-4db6-87f3-b41c80967445","resolution":{"observed_at":"2026-05-16T19:43:33.747222Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"cited_work":{"arxiv_id":"2210.08402","doi":"10.48550/arxiv.2210.08402","metadata_source":"pith","pith_arxiv_id":"2210.08402","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","venue":"cs.CV","work_id":"1d19deb4-3043-409d-b901-f047c51a323b","year":2022},"citing_paper":{"arxiv_id":"2409.17146","last_updated":"2024-12-05T14:28:40Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-09-25T17:59:51Z","title":"Molmo and PixMo: Open Weights and Open Data for State-of-the-Art Vision-Language Models","version":2},"reference_index":98,"source":"pdf_text","source_observed_at":"2026-05-15T01:55:12.501409Z"},"links":{"cited_paper":"/paper/2210.08402","citing_paper":"/paper/2409.17146"},"observation_digest":"sha256:ccc56efb611895e9fde0d1cc2f00d95fbc0461594085000da79771024b9fae22","observation_id":"e717be9b-542a-4e2a-a2b6-0b48076ffc46","resolution":{"observed_at":"2026-05-15T01:55:12.684621Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2210.08402","snapshot_observed_at":"2026-08-12T16:45:47.334727Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models, 2022","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2411.13211","last_updated":"2024-11-21T16:37:32Z","snapshot_observed_at":"2026-08-17T18:06:30.205840Z","submitted_at":"2024-11-20T11:19:22Z","title":"ViSTa Dataset: Do vision-language models understand sequential tasks?","version":2},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-12T16:45:47.334727Z"},"links":{"cited_paper":"/paper/2210.08402","citing_paper":"/paper/2411.13211"},"observation_digest":"sha256:e69b4dd91b387fd1cb9035951def8cfa3dfdd6484138fd70dd367dcbec7128f6","observation_id":"7cb16373-0c7a-453d-b7b7-d9eb3609c871","resolution":{"observed_at":"2026-08-12T16:45:47.334727Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2210.08402","snapshot_observed_at":"2026-08-12T14:14:17.652856Z","title":"Laion-5b: An open large-scale dataset for training next generation image-text models","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2411.15551","last_updated":"2024-11-23T13:17:00Z","snapshot_observed_at":"2026-08-17T10:23:22.126384Z","submitted_at":"2024-11-23T13:17:00Z","title":"NeRF Inpainting with Geometric Diffusion Prior and Balanced Score Distillation","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-12T14:14:17.652856Z"},"links":{"cited_paper":"/paper/2210.08402","citing_paper":"/paper/2411.15551"},"observation_digest":"sha256:eed62eeda230e81ba1204a94e4f23cf4ac1e27cd327c65cab1e2ee36c8d735db","observation_id":"d800243e-93d7-4378-8612-49ef13fad082","resolution":{"observed_at":"2026-08-12T14:14:17.652856Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2210.08402","snapshot_observed_at":"2026-08-12T10:28:07.619388Z","title":"LAION-5B: An open large-scale dataset for training next gen- eration image-text models","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2411.19261","last_updated":"2025-03-09T13:39:55Z","snapshot_observed_at":"2026-08-19T15:28:44.012410Z","submitted_at":"2024-11-28T16:50:30Z","title":"Improving Multi-Subject Consistency in Open-Domain Image Generation with Isolation and Reposition Attention","version":2},"reference_index":55,"source":"pdf_text","source_observed_at":"2026-08-12T10:28:07.619388Z"},"links":{"cited_paper":"/paper/2210.08402","citing_paper":"/paper/2411.19261"},"observation_digest":"sha256:c964e7c2362a1a865a7528b134178961bde23a7559bbffa3d6272251f337590b","observation_id":"74a68153-adc6-4b97-be52-83170d8be1a4","resolution":{"observed_at":"2026-08-12T10:28:07.619388Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2210.08402","snapshot_observed_at":"2026-08-12T05:33:18.400374Z","title":"Laion-5b: An open large-scale dataset for training next generation image-text models","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2412.00357","last_updated":"2024-11-30T04:37:38Z","snapshot_observed_at":"2026-08-19T10:12:03.990796Z","submitted_at":"2024-11-30T04:37:38Z","title":"Safety Alignment Backfires: Preventing the Re-emergence of Suppressed Concepts in Fine-tuned Text-to-Image Diffusion Models","version":1},"reference_index":71,"source":"pdf_text","source_observed_at":"2026-08-12T05:33:18.400374Z"},"links":{"cited_paper":"/paper/2210.08402","citing_paper":"/paper/2412.00357"},"observation_digest":"sha256:21a47ba20f4c71bb5acb1bbfd777546695d2222303b70583eb4a9ec057a8cab0","observation_id":"65272649-dafc-4d66-9a28-03c0154b5a65","resolution":{"observed_at":"2026-08-12T05:33:18.400374Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2210.08402","snapshot_observed_at":"2026-08-12T04:34:52.597013Z","title":"Laion-5b: An open large-scale dataset for training next generation image-text models","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2412.01271","last_updated":"2025-06-05T10:34:56Z","snapshot_observed_at":"2026-08-13T14:39:27.711270Z","submitted_at":"2024-12-02T08:38:19Z","title":"MuLan: Adapting Multilingual Diffusion Models for Hundreds of Languages with Negligible Cost","version":2},"reference_index":37,"source":"arxiv_source","source_observed_at":"2026-08-12T04:34:52.597013Z"},"links":{"cited_paper":"/paper/2210.08402","citing_paper":"/paper/2412.01271"},"observation_digest":"sha256:1ae6590eb0a38a616298bd83f0f1f2f14bca836df3b1472aa1c0b2a5ee186aac","observation_id":"0729244f-b06b-4311-a8b1-d83c5d583342","resolution":{"observed_at":"2026-08-12T04:34:52.597013Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2210.08402","snapshot_observed_at":"2026-08-11T23:24:36.277668Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2412.02527","last_updated":"2024-12-03T16:21:17Z","snapshot_observed_at":"2026-08-18T10:30:23.195608Z","submitted_at":"2024-12-03T16:21:17Z","title":"The Multimodal Universe: Enabling Large-Scale Machine Learning with 100TB of Astronomical Scientific Data","version":1},"reference_index":125,"source":"pdf_text","source_observed_at":"2026-08-11T23:24:36.277668Z"},"links":{"cited_paper":"/paper/2210.08402","citing_paper":"/paper/2412.02527"},"observation_digest":"sha256:f2d4702d15e35e31c22bba594f6f694777cbf053f7bade28ff2cda9dcda190a4","observation_id":"562d2a38-7654-4f5e-9220-886eca7459fb","resolution":{"observed_at":"2026-08-11T23:24:36.277668Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2210.08402","snapshot_observed_at":"2026-08-11T21:35:11.332122Z","title":"Laion-5b: An open large-scale dataset for training next generation image-text models, 2022a","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2412.04280","last_updated":"2025-05-06T09:56:18Z","snapshot_observed_at":"2026-08-19T18:48:00.054749Z","submitted_at":"2024-12-05T16:00:59Z","title":"HumanEdit: A High-Quality Human-Rewarded Dataset for Instruction-based Image Editing","version":2},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-11T21:35:11.332122Z"},"links":{"cited_paper":"/paper/2210.08402","citing_paper":"/paper/2412.04280"},"observation_digest":"sha256:0d3eb89ce14a120ee755c1c6ced9d3be2731702d2e66158905bedbab30e68f14","observation_id":"d4c2ca67-2619-470a-b4e6-c9f1c4a92dd4","resolution":{"observed_at":"2026-08-11T21:35:11.332122Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2210.08402","snapshot_observed_at":"2026-08-11T17:56:46.222949Z","title":"Amanpreet Singh, Vivek Natarajan, Meet Shah, Yu Jiang, Xinlei Chen, Dhruv Batra, Devi Parikh, and Marcus Rohrbach","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2412.08378","last_updated":"2025-04-30T08:49:56Z","snapshot_observed_at":"2026-08-21T07:48:11.256555Z","submitted_at":"2024-12-11T13:41:21Z","title":"FILA: Fine-Grained Vision Language Models","version":3},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-11T17:56:46.222949Z"},"links":{"cited_paper":"/paper/2210.08402","citing_paper":"/paper/2412.08378"},"observation_digest":"sha256:aefef8bdec2609d8acaa9bdddaff3ee533d3a65512a553665d03daeed404c3e9","observation_id":"f2e99b39-f197-4592-836e-3a76de13f774","resolution":{"observed_at":"2026-08-11T17:56:46.222949Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2210.08402","snapshot_observed_at":"2026-08-11T17:48:01.776849Z","title":null,"venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2412.08573","last_updated":"2025-01-03T11:34:09Z","snapshot_observed_at":"2026-08-17T22:58:03.091524Z","submitted_at":"2024-12-11T17:41:53Z","title":"TryOffAnyone: Tiled Cloth Generation from a Dressed Person","version":2},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-11T17:48:01.776849Z"},"links":{"cited_paper":"/paper/2210.08402","citing_paper":"/paper/2412.08573"},"observation_digest":"sha256:73cbb983ee3f2cc398fa66f248631e395ae9dfdc084d110f3556367ae8bee636","observation_id":"af1e0c69-a1dc-4b07-b8f1-0a90153de8c7","resolution":{"observed_at":"2026-08-11T17:48:01.776849Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2210.08402","snapshot_observed_at":"2026-08-11T15:16:34.177833Z","title":"Laion-5b: An open large-scale dataset for training next generation image-text models","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2412.11198","last_updated":"2024-12-15T14:21:19Z","snapshot_observed_at":"2026-08-21T10:30:28.746918Z","submitted_at":"2024-12-15T14:21:19Z","title":"GEM: A Generalizable Ego-Vision Multimodal World Model for Fine-Grained Ego-Motion, Object Dynamics, and Scene Composition Control","version":1},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-08-11T15:16:34.177833Z"},"links":{"cited_paper":"/paper/2210.08402","citing_paper":"/paper/2412.11198"},"observation_digest":"sha256:401f60dce27519d774c7f67ccb3466dd0344e79f24bf5887a5f998a98a17be1f","observation_id":"cbf2978f-858f-4d31-a3cb-6a31081f7d9b","resolution":{"observed_at":"2026-08-11T15:16:34.177833Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2210.08402","snapshot_observed_at":"2026-08-11T13:38:48.695364Z","title":null,"venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2412.12940","last_updated":"2024-12-17T14:18:50Z","snapshot_observed_at":"2026-08-16T05:17:28.308711Z","submitted_at":"2024-12-17T14:18:50Z","title":"Improving Fine-grained Visual Understanding in VLMs through Text-Only Training","version":1},"reference_index":19,"source":"arxiv_source","source_observed_at":"2026-08-11T13:38:48.695364Z"},"links":{"cited_paper":"/paper/2210.08402","citing_paper":"/paper/2412.12940"},"observation_digest":"sha256:4de5301122872a3f63620f954798485253aff77e7fcbc5964e1076cd409ee175","observation_id":"37f9900e-44ce-4094-870f-d90016f9b138","resolution":{"observed_at":"2026-08-11T13:38:48.695364Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2210.08402","snapshot_observed_at":"2026-08-11T12:15:58.720579Z","title":null,"venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2412.14464","last_updated":"2024-12-19T02:23:55Z","snapshot_observed_at":"2026-08-17T18:09:33.506675Z","submitted_at":"2024-12-19T02:23:55Z","title":"LiftRefine: Progressively Refined View Synthesis from 3D Lifting with Volume-Triplane Representations","version":1},"reference_index":29,"source":"arxiv_source","source_observed_at":"2026-08-11T12:15:58.720579Z"},"links":{"cited_paper":"/paper/2210.08402","citing_paper":"/paper/2412.14464"},"observation_digest":"sha256:424ec1accb95114d307d2c048cfd4b6baddbb5d747945df502aa6766de33f12f","observation_id":"612e0807-b88b-4924-8575-388654d5f300","resolution":{"observed_at":"2026-08-11T12:15:58.720579Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2210.08402","snapshot_observed_at":"2026-08-11T10:32:15.791725Z","title":"Laion- 5b: An open large-scale dataset for training next generation image-text models,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2412.16531","last_updated":"2024-12-21T08:18:43Z","snapshot_observed_at":"2026-08-15T09:04:40.247166Z","submitted_at":"2024-12-21T08:18:43Z","title":"From Creation to Curriculum: Examining the role of generative AI in Arts Universities","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-11T10:32:15.791725Z"},"links":{"cited_paper":"/paper/2210.08402","citing_paper":"/paper/2412.16531"},"observation_digest":"sha256:6acd689c90649b2a3646e1e137a0c0de486f58d32f94c43737b9a057e3bfff8d","observation_id":"d781b9d3-e14e-4fe2-8d13-b2d5f9cf98b1","resolution":{"observed_at":"2026-08-11T10:32:15.791725Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2210.08402","snapshot_observed_at":"2026-08-10T21:24:55.315894Z","title":"CoRR, abs/2210.08402","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2501.05122","last_updated":"2025-01-09T10:26:14Z","snapshot_observed_at":"2026-08-15T07:20:28.361346Z","submitted_at":"2025-01-09T10:26:14Z","title":"Centurio: On Drivers of Multilingual Ability of Large Vision-Language Model","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-10T21:24:55.315894Z"},"links":{"cited_paper":"/paper/2210.08402","citing_paper":"/paper/2501.05122"},"observation_digest":"sha256:7ec0eab51da3ab45fb3b67752b88d61f6ade89ded5d864b05c55b7e6d3fbcded","observation_id":"eaeacd26-3eca-45e9-b94f-98c58ec765e9","resolution":{"observed_at":"2026-08-10T21:24:55.315894Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2210.08402","snapshot_observed_at":"2026-08-10T16:12:24.400494Z","title":"V e n c u, R","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2501.13442","last_updated":"2025-01-23T07:47:00Z","snapshot_observed_at":"2026-08-20T15:15:06.002343Z","submitted_at":"2025-01-23T07:47:00Z","title":"Billion-scale Similarity Search Using a Hybrid Indexing Approach with Advanced Filtering","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-10T16:12:24.400494Z"},"links":{"cited_paper":"/paper/2210.08402","citing_paper":"/paper/2501.13442"},"observation_digest":"sha256:4dcc238f3e6dd5ea8ce76e1f2c8e29ddc2e1350a6c2bf92806df02841d06824a","observation_id":"5da9dc66-c826-44bd-b34c-229f9ea81091","resolution":{"observed_at":"2026-08-10T16:12:24.400494Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2210.08402","snapshot_observed_at":"2026-08-10T15:31:35.705131Z","title":"Laion-5b: An open large-scale dataset for training next generation image-text models","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2501.13920","last_updated":"2025-01-23T18:58:33Z","snapshot_observed_at":"2026-08-19T09:38:20.494324Z","submitted_at":"2025-01-23T18:58:33Z","title":"IMAGINE-E: Image Generation Intelligence Evaluation of State-of-the-art Text-to-Image Models","version":1},"reference_index":68,"source":"pdf_text","source_observed_at":"2026-08-10T15:31:35.705131Z"},"links":{"cited_paper":"/paper/2210.08402","citing_paper":"/paper/2501.13920"},"observation_digest":"sha256:204fa0c1b1d21753ca82729668dec6f3ac30ee3eba2263f04f09ba0ca26840cd","observation_id":"f54c9011-7ba0-4318-9659-e3d16a50ebf4","resolution":{"observed_at":"2026-08-10T15:31:35.705131Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2210.08402","snapshot_observed_at":"2026-08-10T15:32:48.324135Z","title":"Laion-5b: An open large-scale dataset for training next generation image-text models, 2022","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2501.13921","last_updated":"2025-02-11T16:48:15Z","snapshot_observed_at":"2026-08-20T16:03:51.888998Z","submitted_at":"2025-01-23T18:59:02Z","title":"The Breeze 2 Herd of Models: Traditional Chinese LLMs Based on Llama with Vision-Aware and Function-Calling Capabilities","version":3},"reference_index":28,"source":"arxiv_source","source_observed_at":"2026-08-10T15:32:48.324135Z"},"links":{"cited_paper":"/paper/2210.08402","citing_paper":"/paper/2501.13921"},"observation_digest":"sha256:6e61c3c374d0186aab2166960b1271cf6d03b38fb200a026b54479ecfe9243ed","observation_id":"0ff10ebe-c388-4179-8b81-b40282c1f843","resolution":{"observed_at":"2026-08-10T15:32:48.324135Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2210.08402","snapshot_observed_at":"2026-08-10T15:08:01.423096Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models, 2022","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2501.14524","last_updated":"2025-04-04T09:23:37Z","snapshot_observed_at":"2026-08-14T13:03:02.347382Z","submitted_at":"2025-01-24T14:27:12Z","title":"Training-Free Style and Content Transfer by Leveraging U-Net Skip Connections in Stable Diffusion","version":2},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-10T15:08:01.423096Z"},"links":{"cited_paper":"/paper/2210.08402","citing_paper":"/paper/2501.14524"},"observation_digest":"sha256:f9bcf932d6c910043ed0f586699a4c797895bc541ce3929a408773d8a941324b","observation_id":"7b339a8a-da47-4378-ac12-58eda6d7728a","resolution":{"observed_at":"2026-08-10T15:08:01.423096Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2210.08402","snapshot_observed_at":"2026-08-10T14:22:06.095758Z","title":"Laion-5b: An open large-scale dataset for training next generation image-text models","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2501.15434","last_updated":"2025-01-26T07:32:39Z","snapshot_observed_at":"2026-08-15T06:49:21.966767Z","submitted_at":"2025-01-26T07:32:39Z","title":"Mitigating Spurious Negative Pairs for Robust Industrial Anomaly Detection","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-10T14:22:06.095758Z"},"links":{"cited_paper":"/paper/2210.08402","citing_paper":"/paper/2501.15434"},"observation_digest":"sha256:0130d83f4aa8830791eeafb5f6559f4c5d261dcaa834bd6f24ab4a0787f92e6e","observation_id":"4be99cbb-64da-4e54-b198-b84a74878f43","resolution":{"observed_at":"2026-08-10T14:22:06.095758Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2210.08402","snapshot_observed_at":"2026-08-10T05:29:03.160647Z","title":"Laion-5b: An open large-scale dataset for training next generation image-text models","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2501.16971","last_updated":"2025-01-28T14:13:17Z","snapshot_observed_at":"2026-08-16T12:58:36.250407Z","submitted_at":"2025-01-28T14:13:17Z","title":"RODEO: Robust Outlier Detection via Exposing Adaptive Out-of-Distribution Samples","version":1},"reference_index":86,"source":"arxiv_source","source_observed_at":"2026-08-10T05:29:03.160647Z"},"links":{"cited_paper":"/paper/2210.08402","citing_paper":"/paper/2501.16971"},"observation_digest":"sha256:cb32dbee94794f574a5ad0f90e73f3af9539d165c6e22891c86ad0f42a4ed53a","observation_id":"61cc1bb2-225b-48c4-b3c0-64f19acf95ba","resolution":{"observed_at":"2026-08-10T05:29:03.160647Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2210.08402","snapshot_observed_at":"2026-08-16T12:19:28.106999Z","title":"Laion-5b: An open large-scale dataset for training next generation image-text models","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2504.13123","last_updated":"2025-05-17T06:50:58Z","snapshot_observed_at":"2026-08-18T10:36:13.312296Z","submitted_at":"2025-04-17T17:40:06Z","title":"Low-hallucination Synthetic Captions for Large-Scale Vision-Language Model Pre-training","version":2},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-16T12:19:28.106999Z"},"links":{"cited_paper":"/paper/2210.08402","citing_paper":"/paper/2504.13123"},"observation_digest":"sha256:d14f75d7f0f84e883186f8c5af871dd0f34a2ef8a9545eb96eda4192c60f3fe9","observation_id":"df753a51-f896-4d75-a577-43a4884a0720","resolution":{"observed_at":"2026-08-16T12:19:28.106999Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2210.08402","snapshot_observed_at":"2026-08-16T00:54:39.427677Z","title":"Laion-5b: An open large-scale dataset for training next generation image-text models.arXiv preprint arXiv:2210.08402,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2505.02471","last_updated":"2025-06-13T03:49:59Z","snapshot_observed_at":"2026-08-17T07:24:53.039261Z","submitted_at":"2025-05-05T08:56:12Z","title":"Ming-Lite-Uni: Advancements in Unified Architecture for Natural Multimodal Interaction","version":3},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-16T00:54:39.427677Z"},"links":{"cited_paper":"/paper/2210.08402","citing_paper":"/paper/2505.02471"},"observation_digest":"sha256:a07c9aa228e4e0a34b25524743be6b44004bdfeca0ce7b279deb64935869b72d","observation_id":"56fd9f63-719c-4e28-8991-baa5cce05475","resolution":{"observed_at":"2026-08-16T00:54:39.427677Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2210.08402","snapshot_observed_at":"2026-08-15T22:36:58.368758Z","title":null,"venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2505.06761","last_updated":"2025-05-15T15:32:55Z","snapshot_observed_at":"2026-08-20T06:05:38.554768Z","submitted_at":"2025-05-10T21:42:24Z","title":"Learning Graph Representation of Agent Diffusers","version":2},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-15T22:36:58.368758Z"},"links":{"cited_paper":"/paper/2210.08402","citing_paper":"/paper/2505.06761"},"observation_digest":"sha256:8591baa302aa505919bf7fca4381d09aaf0080b87e7c6cd9ad377f95dc233b39","observation_id":"fc4557d9-aaf3-4e05-a4c4-a31a09e56976","resolution":{"observed_at":"2026-08-15T22:36:58.368758Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2210.08402","snapshot_observed_at":"2026-08-15T22:11:08.619893Z","title":"LAION-5B: An open large-scale dataset for training next generation image- text models","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2505.08138","last_updated":"2025-05-13T00:23:17Z","snapshot_observed_at":"2026-08-18T17:58:42.995276Z","submitted_at":"2025-05-13T00:23:17Z","title":"Mirror Mirror on the Wall, Have I Forgotten it All? A New Framework for Evaluating Machine Unlearning","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-15T22:11:08.619893Z"},"links":{"cited_paper":"/paper/2210.08402","citing_paper":"/paper/2505.08138"},"observation_digest":"sha256:e4445533a14f89ba17231fbccb34405810c5bf3228a5212caa1f4574cd1c93cd","observation_id":"4de8e885-ca38-4215-bf65-0874bb46f07b","resolution":{"observed_at":"2026-08-15T22:11:08.619893Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2210.08402","snapshot_observed_at":"2026-08-15T20:53:25.787543Z","title":"Laion-5b: An open large-scale dataset for training next generation image-text models","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2505.11825","last_updated":"2025-05-17T04:17:48Z","snapshot_observed_at":"2026-08-21T03:50:21.014791Z","submitted_at":"2025-05-17T04:17:48Z","title":"Bootstrapping Diffusion: Diffusion Model Training Leveraging Partial and Corrupted Data","version":1},"reference_index":31,"source":"arxiv_source","source_observed_at":"2026-08-15T20:53:25.787543Z"},"links":{"cited_paper":"/paper/2210.08402","citing_paper":"/paper/2505.11825"},"observation_digest":"sha256:477e3416d0612ef486d3b773bd09cd4accd4b4c201707a02fb0aeedcafe36d6d","observation_id":"dec37ba6-9df4-4411-ac63-d584064c7762","resolution":{"observed_at":"2026-08-15T20:53:25.787543Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2210.08402","snapshot_observed_at":"2026-08-15T20:35:59.824308Z","title":"Laion-5b: An open large-scale dataset for train- ing next generation image-text models, 2022","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2505.12552","last_updated":"2025-08-29T18:38:29Z","snapshot_observed_at":"2026-08-21T00:34:07.200981Z","submitted_at":"2025-05-18T21:45:06Z","title":"FreqSelect: Frequency-Aware fMRI-to-Image Reconstruction","version":2},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-15T20:35:59.824308Z"},"links":{"cited_paper":"/paper/2210.08402","citing_paper":"/paper/2505.12552"},"observation_digest":"sha256:8b5fb4604491826715306799f96176beb041471d4224c89deeebfe6b23b9b050","observation_id":"54ceec33-9621-4e10-a66d-3a13d3d0aadd","resolution":{"observed_at":"2026-08-15T20:35:59.824308Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2210.08402","snapshot_observed_at":"2026-08-07T14:58:49.484697Z","title":"Laion-5b: An open large-scale dataset for training next generation image-text models","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2505.16725","last_updated":"2025-05-22T14:33:03Z","snapshot_observed_at":"2026-08-21T09:38:03.639956Z","submitted_at":"2025-05-22T14:33:03Z","title":"Masked Conditioning for Deep Generative Models","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-07T14:58:49.484697Z"},"links":{"cited_paper":"/paper/2210.08402","citing_paper":"/paper/2505.16725"},"observation_digest":"sha256:417974213f899156accc7ed959dfb1c96e0cc4781fcce85fabab6ae966e47ff2","observation_id":"9aa01a32-a47b-4061-a067-6fd28f68d857","resolution":{"observed_at":"2026-08-07T14:58:49.484697Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2210.08402","snapshot_observed_at":"2026-08-07T13:10:28.729669Z","title":"Schuhmann, R","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2505.22626","last_updated":"2025-09-09T06:38:19Z","snapshot_observed_at":"2026-08-20T18:36:43.009743Z","submitted_at":"2025-05-28T17:45:05Z","title":"SCIZOR: A Self-Supervised Approach to Data Curation for Large-Scale Imitation Learning","version":2},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-07T13:10:28.729669Z"},"links":{"cited_paper":"/paper/2210.08402","citing_paper":"/paper/2505.22626"},"observation_digest":"sha256:586f29040337fa83b82104329a42c87944676f99b41e1d682d109867b2862c60","observation_id":"9d004bcf-5137-45bd-886a-62804da3e335","resolution":{"observed_at":"2026-08-07T13:10:28.729669Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2210.08402","snapshot_observed_at":"2026-08-07T13:04:54.151600Z","title":null,"venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2505.22792","last_updated":"2025-08-09T10:28:46Z","snapshot_observed_at":"2026-08-17T21:37:45.703700Z","submitted_at":"2025-05-28T19:03:37Z","title":"Rhetorical Text-to-Image Generation via Two-layer Diffusion Policy Optimization","version":2},"reference_index":44,"source":"arxiv_source","source_observed_at":"2026-08-07T13:04:54.151600Z"},"links":{"cited_paper":"/paper/2210.08402","citing_paper":"/paper/2505.22792"},"observation_digest":"sha256:b408c958e6e2f9cc47576febf64b5a3969cc165ee5f89f6c00aeaba22ae3ec3f","observation_id":"a51916ca-1d75-4109-99a6-9b5dddb95350","resolution":{"observed_at":"2026-08-07T13:04:54.151600Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2210.08402","snapshot_observed_at":"2026-08-07T11:26:58.102259Z","title":"Laion-5b: An open large-scale dataset for training next generation image-text models.ArXiv, abs/2210.08402,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.02698","last_updated":"2025-06-06T03:14:26Z","snapshot_observed_at":"2026-08-20T15:31:07.890614Z","submitted_at":"2025-06-03T09:47:22Z","title":"Smoothed Preference Optimization via ReNoise Inversion for Aligning Diffusion Models with Varied Human Preferences","version":2},"reference_index":2021,"source":"pdf_text","source_observed_at":"2026-08-07T11:26:58.102259Z"},"links":{"cited_paper":"/paper/2210.08402","citing_paper":"/paper/2506.02698"},"observation_digest":"sha256:3c56bffdeb14a1735e4ae9cf162ed7b31eabee8e201b75a95ead03876e206e04","observation_id":"f4c05ef4-1bf4-4432-b848-3c4f87b9da89","resolution":{"observed_at":"2026-08-07T11:26:58.102259Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2210.08402","snapshot_observed_at":"2026-08-07T04:58:09.864477Z","title":"Christoph Schuhmann, Romain Beaumont, Richard V encu, Cade Gordon, Ross Wightman, Mehdi Cherti, Theo Coombes, Aarush Katta, Clayton Mullis, Mitchell Wortsman, et al","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.09344","last_updated":"2025-06-11T02:50:49Z","snapshot_observed_at":"2026-08-08T17:53:50.843512Z","submitted_at":"2025-06-11T02:50:49Z","title":"Ming-Omni: A Unified Multimodal Model for Perception and Generation","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-07T04:58:09.864477Z"},"links":{"cited_paper":"/paper/2210.08402","citing_paper":"/paper/2506.09344"},"observation_digest":"sha256:9103200c7e9239ec9f48d2886b54be9e4248c4db591a852648942b9634cac519","observation_id":"c07e59de-411a-49eb-bf6f-bea0b08dda42","resolution":{"observed_at":"2026-08-07T04:58:09.864477Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2210.08402","snapshot_observed_at":"2026-08-15T19:39:32.982045Z","title":"Laion-5b: An open large-scale dataset for training next generation image-text models","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.15563","last_updated":"2025-06-18T15:39:02Z","snapshot_observed_at":"2026-08-18T19:01:29.275839Z","submitted_at":"2025-06-18T15:39:02Z","title":"Control and Realism: Best of Both Worlds in Layout-to-Image without Training","version":1},"reference_index":40,"source":"arxiv_source","source_observed_at":"2026-08-15T19:39:32.982045Z"},"links":{"cited_paper":"/paper/2210.08402","citing_paper":"/paper/2506.15563"},"observation_digest":"sha256:a2b066c05d3cf0033575aa01795d01bdad7546e45e3514799e7e134f3666b676","observation_id":"10d30582-dd04-47e4-ae55-d186736975db","resolution":{"observed_at":"2026-08-15T19:39:32.982045Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2210.08402","snapshot_observed_at":"2026-08-15T18:56:13.150847Z","title":"Laion-5b: An open large-scale dataset for training next generation image-text models,","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2506.18325","last_updated":"2025-06-23T06:17:30Z","snapshot_observed_at":"2026-08-19T01:10:40.849408Z","submitted_at":"2025-06-23T06:17:30Z","title":"NSFW-Classifier Guided Prompt Sanitization for Safe Text-to-Image Generation","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-15T18:56:13.150847Z"},"links":{"cited_paper":"/paper/2210.08402","citing_paper":"/paper/2506.18325"},"observation_digest":"sha256:0e93ea5dfa1029440d0b05c7dee4b025c8dd71ea8c40482198e3f9d7a2c4474d","observation_id":"1b4e4d9b-6e79-4a45-92e0-30a045ac9c60","resolution":{"observed_at":"2026-08-15T18:56:13.150847Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2210.08402","snapshot_observed_at":"2026-08-06T21:51:56.863163Z","title":"Laion-5b: An open large-scale dataset for training next generation image-text models","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.23283","last_updated":"2025-06-29T15:14:55Z","snapshot_observed_at":"2026-08-18T10:35:06.345741Z","submitted_at":"2025-06-29T15:14:55Z","title":"MoMa: Modulating Mamba for Adapting Image Foundation Models to Video Recognition","version":1},"reference_index":62,"source":"pdf_text","source_observed_at":"2026-08-06T21:51:56.863163Z"},"links":{"cited_paper":"/paper/2210.08402","citing_paper":"/paper/2506.23283"},"observation_digest":"sha256:d980e1614f8393b19caac69b9d698db722876bdeb834a001e0929850a11ca6cc","observation_id":"7c17898b-796b-46d0-afdd-8836a651f2b1","resolution":{"observed_at":"2026-08-06T21:51:56.863163Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2210.08402","snapshot_observed_at":"2026-08-06T21:46:28.873909Z","title":"Laion-5b: An open large-scale dataset for training next generation image-text models, 2022","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2506.23589","last_updated":"2025-06-30T07:51:58Z","snapshot_observed_at":"2026-08-11T16:25:47.851476Z","submitted_at":"2025-06-30T07:51:58Z","title":"Transition Matching: Scalable and Flexible Generative Modeling","version":1},"reference_index":37,"source":"arxiv_source","source_observed_at":"2026-08-06T21:46:28.873909Z"},"links":{"cited_paper":"/paper/2210.08402","citing_paper":"/paper/2506.23589"},"observation_digest":"sha256:b4f6ab21fea28192ea0daaa8a64077f808d9be124a0ebcb16d3ac250935c6b8f","observation_id":"8a95ecd9-ec97-4dc0-a7b1-c2cb674e16b4","resolution":{"observed_at":"2026-08-06T21:46:28.873909Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2210.08402","snapshot_observed_at":"2026-08-06T19:50:21.801084Z","title":"Webster, R., Rabin, J., Simon, L., and Jurie, F","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2507.05300","last_updated":"2025-07-07T01:18:40Z","snapshot_observed_at":"2026-08-17T01:20:08.939356Z","submitted_at":"2025-07-07T01:18:40Z","title":"Structured Captions Improve Prompt Adherence in Text-to-Image Models (Re-LAION-Caption 19M)","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-06T19:50:21.801084Z"},"links":{"cited_paper":"/paper/2210.08402","citing_paper":"/paper/2507.05300"},"observation_digest":"sha256:2736c8c1d67c7df5e60af049bebf75f7b0087eba291c7d0aadea78dcba075df4","observation_id":"3f51bf79-9eea-43ce-8bfd-cd8cdc3a2d0a","resolution":{"observed_at":"2026-08-06T19:50:21.801084Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"cited_work":{"arxiv_id":"2210.08402","doi":"10.48550/arxiv.2210.08402","metadata_source":"pith","pith_arxiv_id":"2210.08402","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","venue":"cs.CV","work_id":"1d19deb4-3043-409d-b901-f047c51a323b","year":2022},"citing_paper":{"arxiv_id":"2507.10236","last_updated":"2026-05-15T17:35:28Z","snapshot_observed_at":"2026-08-15T17:44:11.696115Z","submitted_at":"2025-07-14T12:56:55Z","title":"Navigating the Challenges of AI-Generated Image Detection in the Wild: What Truly Matters?","version":2},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-05-21T23:31:40.691896Z"},"links":{"cited_paper":"/paper/2210.08402","citing_paper":"/paper/2507.10236"},"observation_digest":"sha256:0b2acdd5b6514958a6c96fb9d3b14ca132595d9de165515bb79ba28b0b174741","observation_id":"1e5199ac-dab6-4d35-9d48-5fcedbdc5db9","resolution":{"observed_at":"2026-05-21T23:34:26.521362Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2210.08402","snapshot_observed_at":"2026-08-06T13:56:26.939298Z","title":"LAION-5B: An Open Large-Scale Dataset for Training Next Generation Image-Text Models","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2507.20025","last_updated":"2025-07-26T17:47:09Z","snapshot_observed_at":"2026-08-14T03:40:16.418966Z","submitted_at":"2025-07-26T17:47:09Z","title":"Region-based Cluster Discrimination for Visual Representation Learning","version":1},"reference_index":57,"source":"pdf_text","source_observed_at":"2026-08-06T13:56:26.939298Z"},"links":{"cited_paper":"/paper/2210.08402","citing_paper":"/paper/2507.20025"},"observation_digest":"sha256:9670b882bc12d4e6c8d4642c88775440435399edbfb792ee04f50a77a2a2fe0c","observation_id":"b0ed33ef-de76-4f7c-befc-f9cf0b90222e","resolution":{"observed_at":"2026-08-06T13:56:26.939298Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2210.08402","snapshot_observed_at":"2026-08-06T04:23:07.177967Z","title":"Laion-5b: An open large-scale dataset for training next generation image-text models","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2508.03789","last_updated":"2025-08-22T08:53:37Z","snapshot_observed_at":"2026-08-16T17:02:25.152374Z","submitted_at":"2025-08-05T17:17:13Z","title":"HPSv3: Towards Wide-Spectrum Human Preference Score","version":2},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-06T04:23:07.177967Z"},"links":{"cited_paper":"/paper/2210.08402","citing_paper":"/paper/2508.03789"},"observation_digest":"sha256:fd410360bd365a15a63709c86cd87a69c9d37d6fc5998271b9c26aab3c7452e7","observation_id":"f9f1caf8-e4a0-4114-9dda-3b9ea13e0c0c","resolution":{"observed_at":"2026-08-06T04:23:07.177967Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2210.08402","snapshot_observed_at":"2026-08-05T21:25:54.359107Z","title":null,"venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2508.08754","last_updated":"2025-08-12T09:02:10Z","snapshot_observed_at":"2026-08-14T04:58:04.266311Z","submitted_at":"2025-08-12T09:02:10Z","title":"Exploring Palette based Color Guidance in Diffusion Models","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-05T21:25:54.359107Z"},"links":{"cited_paper":"/paper/2210.08402","citing_paper":"/paper/2508.08754"},"observation_digest":"sha256:f135194f5bdef2879bf506cc9ec6c0d87912169fda05f43f6908bafeaa885c12","observation_id":"5b2a5573-1eff-483d-a5ed-ccebe7a40f86","resolution":{"observed_at":"2026-08-05T21:25:54.359107Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2210.08402","snapshot_observed_at":"2026-08-05T18:40:36.129787Z","title":null,"venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2508.14405","last_updated":"2025-08-20T04:03:54Z","snapshot_observed_at":"2026-08-12T20:54:11.106446Z","submitted_at":"2025-08-20T04:03:54Z","title":"CTA-Flux: Integrating Chinese Cultural Semantics into High-Quality English Text-to-Image Communities","version":1},"reference_index":35,"source":"arxiv_source","source_observed_at":"2026-08-05T18:40:36.129787Z"},"links":{"cited_paper":"/paper/2210.08402","citing_paper":"/paper/2508.14405"},"observation_digest":"sha256:2617424ad937b99e4dfc32895258d114b6dd6f23c40d5989a7dd5855b54ba459","observation_id":"326d4148-59eb-466b-9700-ce0a2ecfde25","resolution":{"observed_at":"2026-08-05T18:40:36.129787Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2210.08402","snapshot_observed_at":"2026-08-05T13:11:56.902333Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2509.00849","last_updated":"2025-08-31T13:46:16Z","snapshot_observed_at":"2026-08-21T03:13:52.842932Z","submitted_at":"2025-08-31T13:46:16Z","title":"Prompting Away Stereotypes? Evaluating Bias in Text-to-Image Models for Occupations","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-05T13:11:56.902333Z"},"links":{"cited_paper":"/paper/2210.08402","citing_paper":"/paper/2509.00849"},"observation_digest":"sha256:291359fd4fa6bd57cdde764db854d9cf027a2b30bd3ecb7dea85809d8db4ae32","observation_id":"28f79eb1-7a1b-44a9-9d3f-fb158ba8bf86","resolution":{"observed_at":"2026-08-05T13:11:56.902333Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2210.08402","snapshot_observed_at":"2026-08-05T10:59:25.401255Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2509.03385","last_updated":"2025-09-03T15:02:40Z","snapshot_observed_at":"2026-08-21T21:14:21.780411Z","submitted_at":"2025-09-03T15:02:40Z","title":"Human Preference-Aligned Concept Customization Benchmark via Decomposed Evaluation","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-05T10:59:25.401255Z"},"links":{"cited_paper":"/paper/2210.08402","citing_paper":"/paper/2509.03385"},"observation_digest":"sha256:0a75592f44d40a466f1d9de334acd7942846977fcc15cbe470dfafa2f95b36ea","observation_id":"298eef0a-a9b1-4daa-aeac-a70f9402e00c","resolution":{"observed_at":"2026-08-05T10:59:25.401255Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2210.08402","snapshot_observed_at":"2026-08-15T15:49:57.073267Z","title":"Laion-5b: An open large-scale dataset for training next generation image-text models, 2022","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2509.21079","last_updated":"2026-08-01T05:07:06Z","snapshot_observed_at":"2026-08-15T15:44:46.911571Z","submitted_at":"2025-09-25T12:28:22Z","title":"SoM-1K: A Thousand-Problem Benchmark Dataset for Strength of Materials","version":2},"reference_index":37,"source":"arxiv_source","source_observed_at":"2026-08-15T15:49:57.073267Z"},"links":{"cited_paper":"/paper/2210.08402","citing_paper":"/paper/2509.21079"},"observation_digest":"sha256:2af05e22a031f39d95495cc8e6ffbf952b97c0c0e660f45181a29f8b0b2a17df","observation_id":"ce9a9413-e49b-4e41-9027-de9e50bb0878","resolution":{"observed_at":"2026-08-15T15:49:57.073267Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"cited_work":{"arxiv_id":"2210.08402","doi":"10.48550/arxiv.2210.08402","metadata_source":"pith","pith_arxiv_id":"2210.08402","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","venue":"cs.CV","work_id":"1d19deb4-3043-409d-b901-f047c51a323b","year":2022},"citing_paper":{"arxiv_id":"2510.02307","last_updated":"2026-05-14T21:42:02Z","snapshot_observed_at":"2026-08-16T19:39:40.493272Z","submitted_at":"2025-10-02T17:59:43Z","title":"NoiseShift: Resolution-Aware Noise Recalibration for Better Low-Resolution Image Generation","version":2},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-05-21T21:41:29.502472Z"},"links":{"cited_paper":"/paper/2210.08402","citing_paper":"/paper/2510.02307"},"observation_digest":"sha256:6ab6059ed665c0000133df84344816bdbf259c568fe411f31172228cb8dc96d8","observation_id":"6f2413fd-9ff5-4885-a321-8d0a1c2c8f65","resolution":{"observed_at":"2026-05-21T21:44:22.965412Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2210.08402","snapshot_observed_at":"2026-08-03T21:34:14.601061Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models.arXivpreprintarXiv:2210.08402,2022","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2511.14993","last_updated":"2026-05-26T15:07:50Z","snapshot_observed_at":"2026-08-15T09:14:33.846886Z","submitted_at":"2025-11-19T00:23:22Z","title":"Kandinsky 5.0: A Family of Foundation Models for Image and Video Generation","version":3},"reference_index":64,"source":"pdf_text","source_observed_at":"2026-08-03T21:34:14.601061Z"},"links":{"cited_paper":"/paper/2210.08402","citing_paper":"/paper/2511.14993"},"observation_digest":"sha256:8aef606cea6c44448d9b45e54d6019b9e6b3696164ff9137e5ebf6e1bbce0861","observation_id":"63d3e7d5-4c00-4971-93a7-9de517d3f0f5","resolution":{"observed_at":"2026-08-03T21:34:14.601061Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2210.08402","snapshot_observed_at":"2026-08-03T18:48:55.845527Z","title":null,"venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2512.03553","last_updated":"2026-06-03T10:10:35Z","snapshot_observed_at":"2026-08-17T07:59:13.935518Z","submitted_at":"2025-12-03T08:20:58Z","title":"Dynamic Content Moderation in Livestreams: Combining Supervised Classification with MLLM-Boosted Similarity Matching","version":3},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-03T18:48:55.845527Z"},"links":{"cited_paper":"/paper/2210.08402","citing_paper":"/paper/2512.03553"},"observation_digest":"sha256:46be2918bb305e7ac528b9eb7ce41c51a70b593acfc0183fb3280b4518aaf98a","observation_id":"98adec54-6e9d-4a82-9009-f91bfb280080","resolution":{"observed_at":"2026-08-03T18:48:55.845527Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"cited_work":{"arxiv_id":"2210.08402","doi":"10.48550/arxiv.2210.08402","metadata_source":"pith","pith_arxiv_id":"2210.08402","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","venue":"cs.CV","work_id":"1d19deb4-3043-409d-b901-f047c51a323b","year":2022},"citing_paper":{"arxiv_id":"2602.13310","last_updated":"2026-05-07T08:00:36Z","snapshot_observed_at":"2026-08-03T02:11:51.693223Z","submitted_at":"2026-02-10T03:53:25Z","title":"Visual Para-Thinker: Divide-and-Conquer Reasoning for Visual Comprehension","version":2},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-05-16T03:27:53.694506Z"},"links":{"cited_paper":"/paper/2210.08402","citing_paper":"/paper/2602.13310"},"observation_digest":"sha256:f70a3305ec117cf73b0315016daf08352834f001b07991168ede18fb5ee6319f","observation_id":"9f602728-e20d-4ec7-bc30-3707672057e3","resolution":{"observed_at":"2026-05-16T03:30:32.971558Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2210.08402","snapshot_observed_at":"2026-08-02T22:25:59.535987Z","title":"Laion-5b: An open large-scale dataset for training next generation image-text models.ArXiv, abs/2210.08402,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2602.16918","last_updated":"2026-07-13T23:32:16Z","snapshot_observed_at":"2026-08-17T15:57:08.667030Z","submitted_at":"2026-02-18T22:22:44Z","title":"Xray-Visual Models: Scaling Vision models on Industry Scale Data","version":2},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-02T22:25:59.535987Z"},"links":{"cited_paper":"/paper/2210.08402","citing_paper":"/paper/2602.16918"},"observation_digest":"sha256:050657ec5e73b0e7f34d2de61277119e81eef3ac86a5c5cbe76b30d9908fc49e","observation_id":"696c96a6-75cc-40bf-b530-93bb54c9f38a","resolution":{"observed_at":"2026-08-02T22:25:59.535987Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"cited_work":{"arxiv_id":"2210.08402","doi":"10.48550/arxiv.2210.08402","metadata_source":"pith","pith_arxiv_id":"2210.08402","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","venue":"cs.CV","work_id":"1d19deb4-3043-409d-b901-f047c51a323b","year":2022},"citing_paper":{"arxiv_id":"2603.14186","last_updated":"2026-05-07T22:04:09Z","snapshot_observed_at":"2026-08-17T08:32:04.483099Z","submitted_at":"2026-03-15T02:22:27Z","title":"Setting-Matched and Semantics-Scaled Benchmarking of One-Step Generative Models Against Multistep Diffusion and Flow Models","version":4},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-05-15T12:15:38.186914Z"},"links":{"cited_paper":"/paper/2210.08402","citing_paper":"/paper/2603.14186"},"observation_digest":"sha256:ecaf917697627110fcec8b140197ebf9203ea41d3fe114f7bc05ca39db690d5b","observation_id":"e6fc444b-c946-497f-9b7c-8d1eabd8cd33","resolution":{"observed_at":"2026-05-15T12:20:00.137541Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2210.08402","snapshot_observed_at":"2026-08-03T02:31:03.143146Z","title":null,"venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2604.01207","last_updated":"2026-07-31T06:47:55Z","snapshot_observed_at":"2026-08-13T01:45:01.629353Z","submitted_at":"2026-04-01T17:51:00Z","title":"TRACE: High-Fidelity 3D Scene Editing via Tangible Reconstruction and Geometry-Aligned Contextual Video Masking","version":2},"reference_index":74,"source":"pdf_text","source_observed_at":"2026-08-03T02:31:03.143146Z"},"links":{"cited_paper":"/paper/2210.08402","citing_paper":"/paper/2604.01207"},"observation_digest":"sha256:0417855b8b49d38fc787997cc81e68fe227637d573595198856692c50c75c31b","observation_id":"f4ee9eda-5667-41e5-b314-ccefd3b21734","resolution":{"observed_at":"2026-08-03T02:31:03.143146Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"cited_work":{"arxiv_id":"2210.08402","doi":"10.48550/arxiv.2210.08402","metadata_source":"pith","pith_arxiv_id":"2210.08402","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","venue":"cs.CV","work_id":"1d19deb4-3043-409d-b901-f047c51a323b","year":2022},"citing_paper":{"arxiv_id":"2604.08212","last_updated":"2026-04-09T13:11:30Z","snapshot_observed_at":"2026-08-15T03:03:20.099914Z","submitted_at":"2026-04-09T13:11:30Z","title":"Vision-Language Foundation Models for Comprehensive Automated Pavement Condition Assessment","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-05-10T17:30:39.410040Z"},"links":{"cited_paper":"/paper/2210.08402","citing_paper":"/paper/2604.08212"},"observation_digest":"sha256:c89976cb344de4dd7cd7d0de89ba78ca985d298217296f87a14fa44eb093741b","observation_id":"d3826578-e180-4f1c-b2d7-b69a94d92eb4","resolution":{"observed_at":"2026-05-13T14:22:17.864689Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"cited_work":{"arxiv_id":"2210.08402","doi":"10.48550/arxiv.2210.08402","metadata_source":"pith","pith_arxiv_id":"2210.08402","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","venue":"cs.CV","work_id":"1d19deb4-3043-409d-b901-f047c51a323b","year":2022},"citing_paper":{"arxiv_id":"2604.10954","last_updated":"2026-04-13T03:50:56Z","snapshot_observed_at":"2026-08-13T13:55:01.062987Z","submitted_at":"2026-04-13T03:50:56Z","title":"FineEdit: Fine-Grained Image Edit with Bounding Box Guidance","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-05-10T16:15:23.578176Z"},"links":{"cited_paper":"/paper/2210.08402","citing_paper":"/paper/2604.10954"},"observation_digest":"sha256:c32bbaf2e8e8d94d15c0c6080f0ea3b84724cf41c867ccaa616ba4850f9bda75","observation_id":"08ba0d6f-39f0-41b8-b433-068fa8b1eb07","resolution":{"observed_at":"2026-05-13T14:22:17.864689Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"cited_work":{"arxiv_id":"2210.08402","doi":"10.48550/arxiv.2210.08402","metadata_source":"pith","pith_arxiv_id":"2210.08402","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","venue":"cs.CV","work_id":"1d19deb4-3043-409d-b901-f047c51a323b","year":2022},"citing_paper":{"arxiv_id":"2604.11789","last_updated":"2026-04-20T14:38:53Z","snapshot_observed_at":"2026-08-09T05:10:13.009841Z","submitted_at":"2026-04-13T17:55:02Z","title":"LMMs Meet Object-Centric Vision: Understanding, Segmentation, Editing and Generation","version":2},"reference_index":143,"source":"pdf_text","source_observed_at":"2026-05-10T15:35:37.095627Z"},"links":{"cited_paper":"/paper/2210.08402","citing_paper":"/paper/2604.11789"},"observation_digest":"sha256:d8003e183b2828068696022c77e606fcb257bf5955379a8951d4f22f13af8669","observation_id":"d62745f6-85cc-4671-9ace-ef52ace419b0","resolution":{"observed_at":"2026-05-13T14:22:17.864689Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"cited_work":{"arxiv_id":"2210.08402","doi":"10.48550/arxiv.2210.08402","metadata_source":"pith","pith_arxiv_id":"2210.08402","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","venue":"cs.CV","work_id":"1d19deb4-3043-409d-b901-f047c51a323b","year":2022},"citing_paper":{"arxiv_id":"2604.21977","last_updated":"2026-04-23T18:00:03Z","snapshot_observed_at":"2026-08-12T21:39:55.197410Z","submitted_at":"2026-04-23T18:00:03Z","title":"Euclid Quick Data Release (Q1). AstroVink: A vision transformer approach to find strong gravitational lens systems","version":1},"reference_index":59,"source":"arxiv_source","source_observed_at":"2026-05-08T14:02:17.885354Z"},"links":{"cited_paper":"/paper/2210.08402","citing_paper":"/paper/2604.21977"},"observation_digest":"sha256:17bab91bb11efb46a992f80a0222a9719e20a13e43aa528069b551fa942af4f1","observation_id":"1fa9257b-c6d6-4a22-95cf-0dda900f61b6","resolution":{"observed_at":"2026-05-13T14:22:17.864689Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"cited_work":{"arxiv_id":"2210.08402","doi":"10.48550/arxiv.2210.08402","metadata_source":"pith","pith_arxiv_id":"2210.08402","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","venue":"cs.CV","work_id":"1d19deb4-3043-409d-b901-f047c51a323b","year":2022},"citing_paper":{"arxiv_id":"2604.22838","last_updated":"2026-04-21T06:27:18Z","snapshot_observed_at":"2026-08-20T15:55:17.278205Z","submitted_at":"2026-04-21T06:27:18Z","title":"Neural Network Optimization Reimagined: Decoupled Techniques for Scratch and Fine-Tuning","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-05-10T03:26:09.751493Z"},"links":{"cited_paper":"/paper/2210.08402","citing_paper":"/paper/2604.22838"},"observation_digest":"sha256:565e358bdefdc0199fef756c703a03d3eb090bd1c669bb10d032c8091f3784c7","observation_id":"763e1d92-e436-4503-82bd-e5a8fb1fe178","resolution":{"observed_at":"2026-05-13T14:22:17.864689Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"cited_work":{"arxiv_id":"2210.08402","doi":"10.48550/arxiv.2210.08402","metadata_source":"pith","pith_arxiv_id":"2210.08402","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","venue":"cs.CV","work_id":"1d19deb4-3043-409d-b901-f047c51a323b","year":2022},"citing_paper":{"arxiv_id":"2604.23536","last_updated":"2026-04-26T05:16:54Z","snapshot_observed_at":"2026-08-13T03:39:46.544091Z","submitted_at":"2026-04-26T05:16:54Z","title":"$Z^2$-Sampling: Zero-Cost Zigzag Trajectories for Semantic Alignment in Diffusion Models","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-05-08T06:41:04.597012Z"},"links":{"cited_paper":"/paper/2210.08402","citing_paper":"/paper/2604.23536"},"observation_digest":"sha256:76c8a21ac9c9271d589cfdfcba83cae05bd3aebddb7a3f42bc974d21f3726f4c","observation_id":"96e28610-54f9-4d49-a88d-2fc8322381d2","resolution":{"observed_at":"2026-05-13T14:22:17.864689Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"cited_work":{"arxiv_id":"2210.08402","doi":"10.48550/arxiv.2210.08402","metadata_source":"pith","pith_arxiv_id":"2210.08402","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","venue":"cs.CV","work_id":"1d19deb4-3043-409d-b901-f047c51a323b","year":2022},"citing_paper":{"arxiv_id":"2604.23540","last_updated":"2026-04-26T05:32:26Z","snapshot_observed_at":"2026-08-12T18:51:31.849899Z","submitted_at":"2026-04-26T05:32:26Z","title":"Oracle Noise: Faster Semantic Spherical Alignment for Interpretable Latent Optimization","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-05-08T06:58:09.085573Z"},"links":{"cited_paper":"/paper/2210.08402","citing_paper":"/paper/2604.23540"},"observation_digest":"sha256:4c9e18898162838047a262fa442bf237139f2d690c415cecc032926e18b0ce45","observation_id":"607aaf3c-cafc-4dc1-ad82-72fa5e1b6d00","resolution":{"observed_at":"2026-05-13T14:22:17.864689Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"cited_work":{"arxiv_id":"2210.08402","doi":"10.48550/arxiv.2210.08402","metadata_source":"pith","pith_arxiv_id":"2210.08402","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","venue":"cs.CV","work_id":"1d19deb4-3043-409d-b901-f047c51a323b","year":2022},"citing_paper":{"arxiv_id":"2604.26503","last_updated":"2026-04-29T10:08:08Z","snapshot_observed_at":"2026-08-15T19:27:52.761635Z","submitted_at":"2026-04-29T10:08:08Z","title":"Delta Score Matters! Spatial Adaptive Multi Guidance in Diffusion Models","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-05-07T11:08:23.853123Z"},"links":{"cited_paper":"/paper/2210.08402","citing_paper":"/paper/2604.26503"},"observation_digest":"sha256:7be40afb477c71d93252c49d6db5328231899fcdac67096acd038935be951032","observation_id":"29fbfbaa-d564-4a30-a836-85b4fceddf81","resolution":{"observed_at":"2026-05-13T14:22:17.864689Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"cited_work":{"arxiv_id":"2210.08402","doi":"10.48550/arxiv.2210.08402","metadata_source":"pith","pith_arxiv_id":"2210.08402","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","venue":"cs.CV","work_id":"1d19deb4-3043-409d-b901-f047c51a323b","year":2022},"citing_paper":{"arxiv_id":"2605.04227","last_updated":"2026-08-01T20:12:35Z","snapshot_observed_at":"2026-08-15T09:52:14.216260Z","submitted_at":"2026-05-05T19:12:11Z","title":"Pro$^2$Assist: Continuous Step-aware Proactive Assistance with Multi-modal Egocentric Perception for Long-horizon Procedural Tasks","version":1},"reference_index":59,"source":"pdf_text","source_observed_at":"2026-05-08T17:16:31.820718Z"},"links":{"cited_paper":"/paper/2210.08402","citing_paper":"/paper/2605.04227"},"observation_digest":"sha256:2840df4d97d7d68746264eaae05e7d60f9eff5118ef60cd053a6ef65869c12f9","observation_id":"754790a9-8539-4569-a91b-94ea88cb9cfd","resolution":{"observed_at":"2026-05-13T14:22:17.864689Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2210.08402","snapshot_observed_at":"2026-08-04T05:19:56.236602Z","title":null,"venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2605.04227","last_updated":"2026-08-01T20:12:35Z","snapshot_observed_at":"2026-08-15T09:52:14.216260Z","submitted_at":"2026-05-05T19:12:11Z","title":"Pro$^2$Assist: Continuous Step-aware Proactive Assistance with Multi-modal Egocentric Perception for Long-horizon Procedural Tasks","version":2},"reference_index":54,"source":"pdf_text","source_observed_at":"2026-08-04T05:19:56.236602Z"},"links":{"cited_paper":"/paper/2210.08402","citing_paper":"/paper/2605.04227"},"observation_digest":"sha256:f325a2a3f42dcd99520fbedfca7abfbc7d02fce220183f5aed15a57f515b69e1","observation_id":"1eae71fb-3ba6-4624-8692-3c57ec541e8a","resolution":{"observed_at":"2026-08-04T05:19:56.236602Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"cited_work":{"arxiv_id":"2210.08402","doi":"10.48550/arxiv.2210.08402","metadata_source":"pith","pith_arxiv_id":"2210.08402","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","venue":"cs.CV","work_id":"1d19deb4-3043-409d-b901-f047c51a323b","year":2022},"citing_paper":{"arxiv_id":"2605.05348","last_updated":"2026-05-06T18:18:15Z","snapshot_observed_at":"2026-08-15T00:00:33.854821Z","submitted_at":"2026-05-06T18:18:15Z","title":"Making AI Drafts Count: A Quality Threshold in Audio Description Workflows","version":1},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-05-08T16:07:12.813384Z"},"links":{"cited_paper":"/paper/2210.08402","citing_paper":"/paper/2605.05348"},"observation_digest":"sha256:00cf18a72909e22e825d833674edaea188f58c9501a43f130de73d691d7d3cd1","observation_id":"db63e60d-3b24-4fb2-a2db-d4605150ee60","resolution":{"observed_at":"2026-05-13T14:22:17.864689Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"cited_work":{"arxiv_id":"2210.08402","doi":"10.48550/arxiv.2210.08402","metadata_source":"pith","pith_arxiv_id":"2210.08402","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","venue":"cs.CV","work_id":"1d19deb4-3043-409d-b901-f047c51a323b","year":2022},"citing_paper":{"arxiv_id":"2605.05416","last_updated":"2026-05-06T20:20:17Z","snapshot_observed_at":"2026-08-16T11:16:46.129304Z","submitted_at":"2026-05-06T20:20:17Z","title":"From Cradle to Cloud: A Life Cycle Review of AI's Environmental Footprint","version":1},"reference_index":86,"source":"pdf_text","source_observed_at":"2026-05-08T15:43:50.422887Z"},"links":{"cited_paper":"/paper/2210.08402","citing_paper":"/paper/2605.05416"},"observation_digest":"sha256:7464888533615351b19d477c500c6c4aaa1bb1aee2ecbe43bcd9cea3ba0e594e","observation_id":"78027118-0967-4104-9897-ee375c9f7e08","resolution":{"observed_at":"2026-05-13T14:22:17.864689Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"cited_work":{"arxiv_id":"2210.08402","doi":"10.48550/arxiv.2210.08402","metadata_source":"pith","pith_arxiv_id":"2210.08402","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","venue":"cs.CV","work_id":"1d19deb4-3043-409d-b901-f047c51a323b","year":2022},"citing_paper":{"arxiv_id":"2605.06583","last_updated":"2026-05-07T17:12:47Z","snapshot_observed_at":"2026-08-11T08:04:18.772776Z","submitted_at":"2026-05-07T17:12:47Z","title":"Improved techniques for fine-tuning flow models via adjoint matching: a deterministic control pipeline","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-05-08T09:45:00.759474Z"},"links":{"cited_paper":"/paper/2210.08402","citing_paper":"/paper/2605.06583"},"observation_digest":"sha256:1c7ae1b4a604f71f988d3fa91223f8eb23214bdc8139e669fb1793d97a2c0e3d","observation_id":"ea796df5-2961-491e-9698-c0cff32e6ab0","resolution":{"observed_at":"2026-05-13T14:22:17.864689Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"cited_work":{"arxiv_id":"2210.08402","doi":"10.48550/arxiv.2210.08402","metadata_source":"pith","pith_arxiv_id":"2210.08402","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","venue":"cs.CV","work_id":"1d19deb4-3043-409d-b901-f047c51a323b","year":2022},"citing_paper":{"arxiv_id":"2605.11107","last_updated":"2026-05-11T18:13:05Z","snapshot_observed_at":"2026-08-11T03:45:15.335189Z","submitted_at":"2026-05-11T18:13:05Z","title":"Birds of a Feather Flock Together: Background-Invariant Representations via Linear Structure in VLMs","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-05-13T07:26:02.947081Z"},"links":{"cited_paper":"/paper/2210.08402","citing_paper":"/paper/2605.11107"},"observation_digest":"sha256:65ecaf58cb42e275b8da8bcbf3d4cc90c0a6ecc20e46491349b947dca2229d2b","observation_id":"3516045c-353a-4ca7-adf8-b4fe63b3a745","resolution":{"observed_at":"2026-05-13T14:22:17.864689Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"cited_work":{"arxiv_id":"2210.08402","doi":"10.48550/arxiv.2210.08402","metadata_source":"pith","pith_arxiv_id":"2210.08402","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","venue":"cs.CV","work_id":"1d19deb4-3043-409d-b901-f047c51a323b","year":2022},"citing_paper":{"arxiv_id":"2605.13857","last_updated":"2026-04-08T15:42:16Z","snapshot_observed_at":"2026-08-17T01:18:34.418234Z","submitted_at":"2026-04-08T15:42:16Z","title":"MoZoo:Unleashing Video Diffusion power in animal fur and muscle simulation","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-05-15T06:53:13.152677Z"},"links":{"cited_paper":"/paper/2210.08402","citing_paper":"/paper/2605.13857"},"observation_digest":"sha256:06005469753282cd4a3ca3a4c1bc3830cab384e7e3133c7987f3fff75098010b","observation_id":"dba58101-6604-4da3-b7c2-1ca6bb3f86d9","resolution":{"observed_at":"2026-05-15T06:55:10.418336Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"cited_work":{"arxiv_id":"2210.08402","doi":"10.48550/arxiv.2210.08402","metadata_source":"pith","pith_arxiv_id":"2210.08402","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","venue":"cs.CV","work_id":"1d19deb4-3043-409d-b901-f047c51a323b","year":2022},"citing_paper":{"arxiv_id":"2605.20316","last_updated":"2026-05-19T17:59:39Z","snapshot_observed_at":"2026-08-14T07:00:32.462174Z","submitted_at":"2026-05-19T17:59:39Z","title":"FullFlow: Upgrading Text-to-Image Flow Matching Models for Bidirectional Vision--Language Generation","version":1},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-05-21T07:40:36.206754Z"},"links":{"cited_paper":"/paper/2210.08402","citing_paper":"/paper/2605.20316"},"observation_digest":"sha256:deace16b7e2db9757cff4492e05d31f8e6dcca82ae6099dde8f5aed77fd9a356","observation_id":"a071a5a0-9907-4f6e-9adc-4eae7ba35ec0","resolution":{"observed_at":"2026-05-21T07:44:03.043074Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"cited_work":{"arxiv_id":"2210.08402","doi":"10.48550/arxiv.2210.08402","metadata_source":"pith","pith_arxiv_id":"2210.08402","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","venue":"cs.CV","work_id":"1d19deb4-3043-409d-b901-f047c51a323b","year":2022},"citing_paper":{"arxiv_id":"2605.20787","last_updated":"2026-05-25T11:44:54Z","snapshot_observed_at":"2026-08-18T15:01:26.905075Z","submitted_at":"2026-05-20T06:32:55Z","title":"Findings of the Counter Turing Test: AI-Generated Image Detection","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-05-21T05:43:20.457145Z"},"links":{"cited_paper":"/paper/2210.08402","citing_paper":"/paper/2605.20787"},"observation_digest":"sha256:dd13ee9c5104732d7c5f7f7bcb68b1123ae981ef6994137b0a57483be6faaa7b","observation_id":"051d5680-3eff-4c9f-b6e5-cf8d6ab5bf22","resolution":{"observed_at":"2026-05-21T05:43:58.692611Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"cited_work":{"arxiv_id":"2210.08402","doi":"10.48550/arxiv.2210.08402","metadata_source":"pith","pith_arxiv_id":"2210.08402","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","venue":"cs.CV","work_id":"1d19deb4-3043-409d-b901-f047c51a323b","year":2022},"citing_paper":{"arxiv_id":"2605.23996","last_updated":"2026-05-18T05:33:44Z","snapshot_observed_at":"2026-08-08T18:37:06.694185Z","submitted_at":"2026-05-18T05:33:44Z","title":"Brain-to-Image Retrieval and Reconstruction via Multimodal EEG Alignment","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-06-30T19:02:49.795250Z"},"links":{"cited_paper":"/paper/2210.08402","citing_paper":"/paper/2605.23996"},"observation_digest":"sha256:1661d37512ae06c056d2b051e98667ae32ab97210f33977f4873858089c3b39c","observation_id":"2bae26a7-b6b7-4742-9355-80e7bb8131c8","resolution":{"observed_at":"2026-06-30T19:05:00.482634Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"cited_work":{"arxiv_id":"2210.08402","doi":"10.48550/arxiv.2210.08402","metadata_source":"pith","pith_arxiv_id":"2210.08402","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","venue":"cs.CV","work_id":"1d19deb4-3043-409d-b901-f047c51a323b","year":2022},"citing_paper":{"arxiv_id":"2605.24652","last_updated":"2026-05-23T16:42:39Z","snapshot_observed_at":"2026-08-14T17:33:33.384858Z","submitted_at":"2026-05-23T16:42:39Z","title":"AVBench: Human-Aligned and Automated Evaluation Benchmark for Audio-Video Generative Models","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-06-30T13:35:01.226818Z"},"links":{"cited_paper":"/paper/2210.08402","citing_paper":"/paper/2605.24652"},"observation_digest":"sha256:8e17991e90c8f8c0cab33b39df3f0786ccc021a857a5b3426e6a9832db28bba1","observation_id":"223e80ae-1f4e-4695-b610-02facb2c57f8","resolution":{"observed_at":"2026-06-30T13:44:41.253324Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"cited_work":{"arxiv_id":"2210.08402","doi":"10.48550/arxiv.2210.08402","metadata_source":"pith","pith_arxiv_id":"2210.08402","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","venue":"cs.CV","work_id":"1d19deb4-3043-409d-b901-f047c51a323b","year":2022},"citing_paper":{"arxiv_id":"2606.06624","last_updated":"2026-06-08T15:12:03Z","snapshot_observed_at":"2026-08-13T05:41:07.734536Z","submitted_at":"2026-06-04T18:21:03Z","title":"Principles and Practice of Deep Representation Learning: or a Mathematical Theory of Memory","version":2},"reference_index":93,"source":"pdf_text","source_observed_at":"2026-06-28T03:07:52.730713Z"},"links":{"cited_paper":"/paper/2210.08402","citing_paper":"/paper/2606.06624"},"observation_digest":"sha256:8e53368d1a6a8d8af07e58c354a7520f8eeceaa7b5cb7d2793599e0deb2d81e1","observation_id":"b69f684f-6970-49bf-a80e-a9de4fb4e795","resolution":{"observed_at":"2026-07-02T11:46:55.341383Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"cited_work":{"arxiv_id":"2210.08402","doi":"10.48550/arxiv.2210.08402","metadata_source":"pith","pith_arxiv_id":"2210.08402","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","venue":"cs.CV","work_id":"1d19deb4-3043-409d-b901-f047c51a323b","year":2022},"citing_paper":{"arxiv_id":"2606.17030","last_updated":"2026-06-17T13:54:57Z","snapshot_observed_at":"2026-08-18T14:57:25.186447Z","submitted_at":"2026-06-15T17:52:31Z","title":"Qwen-RobotWorld Technical Report: Unifying Embodied World Modeling through Language-Conditioned Video Generation","version":3},"reference_index":57,"source":"arxiv_source","source_observed_at":"2026-06-27T04:19:26.332718Z"},"links":{"cited_paper":"/paper/2210.08402","citing_paper":"/paper/2606.17030"},"observation_digest":"sha256:1aa3077df625be8299a8a3d5ef8a01a4dca0a00985e44451516c2349bf1e7039","observation_id":"8c029bbc-e575-4b3d-8208-df03862d5c4b","resolution":{"observed_at":"2026-07-03T17:18:43.744984Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"cited_work":{"arxiv_id":"2210.08402","doi":"10.48550/arxiv.2210.08402","metadata_source":"pith","pith_arxiv_id":"2210.08402","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","venue":"cs.CV","work_id":"1d19deb4-3043-409d-b901-f047c51a323b","year":2022},"citing_paper":{"arxiv_id":"2606.26458","last_updated":"2026-06-24T23:38:42Z","snapshot_observed_at":"2026-08-16T15:36:17.486303Z","submitted_at":"2026-06-24T23:38:42Z","title":"MKG-RAG-Bench: Benchmarking Retrieval in Multimodal Knowledge Graph-Augmented Generation","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-06-26T01:11:45.657964Z"},"links":{"cited_paper":"/paper/2210.08402","citing_paper":"/paper/2606.26458"},"observation_digest":"sha256:af88b63b0e68021179ef136814802277f2b706f6136a3daadf617ada7a7636a3","observation_id":"6eb2c390-d9db-4510-a6bb-e6cf8f6cfa1c","resolution":{"observed_at":"2026-07-04T15:59:56.585487Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2210.08402","snapshot_observed_at":"2026-07-14T03:31:19.309532Z","title":"arXiv:2210.08402 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.11738","last_updated":"2026-07-13T16:00:03Z","snapshot_observed_at":"2026-08-14T13:23:30.029952Z","submitted_at":"2026-07-13T16:00:03Z","title":"Qwen-Audio-VAE Technical Report","version":1},"reference_index":72,"source":"arxiv_source","source_observed_at":"2026-07-14T03:31:19.309532Z"},"links":{"cited_paper":"/paper/2210.08402","citing_paper":"/paper/2607.11738"},"observation_digest":"sha256:69eae70bb32e54802bfce097ad174e70cc32419f5ee49bc9f83573521f5a6079","observation_id":"fac4ece3-a65c-4171-8bce-2a40e81aa8d0","resolution":{"observed_at":"2026-07-14T03:31:19.309532Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2210.08402","snapshot_observed_at":"2026-07-30T21:02:13.285052Z","title":"Laion-5b: An open large-scale dataset for training next generation image-text models, 2022","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2607.23488","last_updated":"2026-07-26T06:29:48Z","snapshot_observed_at":"2026-08-16T04:31:32.397544Z","submitted_at":"2026-07-26T06:29:48Z","title":"Learning Sampling Parameters for Diffusion Models","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-07-30T21:02:13.285052Z"},"links":{"cited_paper":"/paper/2210.08402","citing_paper":"/paper/2607.23488"},"observation_digest":"sha256:91bb0d847c50db6ecb9ba922d01434a10d0f563a5bb6efaccf89986b92bb7451","observation_id":"e9f7aa2d-de93-42b1-820e-4959b6c1a5c1","resolution":{"observed_at":"2026-07-30T21:02:13.285052Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2210.08402/citation-record","integrity":"/paper/2210.08402/integrity","json":"/paper/2210.08402/citation-record.json","paper":"/paper/2210.08402"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"15https://github.com/lucidrains/DALLE-pytorch 16https://discord.gg/xBPBXfcFHd 17https://gauss-centre.eu 13","venue":null,"work_id":"db84862f-8e48-44f5-a96d-e5da983febf5","year":null},"citing_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-05-13T14:22:16.968028Z"},"links":{"citing_paper":"/paper/2210.08402"},"observation_digest":"sha256:fee62b3caf87f97fae3ab7fabe091c12f3ef0604485e7a0648822d3dbe57e03d","observation_id":"702d5bf1-6f14-4853-96c5-1b7c54ff40f4","resolution":{"observed_at":"2026-05-13T14:22:17.711959Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2204.14198","last_updated":"2022-11-15T23:07:37Z","snapshot_observed_at":"2026-08-17T03:00:38.806206Z","submitted_at":"2022-04-29T16:29:01Z","title":"Flamingo: a Visual Language Model for Few-Shot Learning","version":2},"cited_work":{"arxiv_id":"2204.14198","doi":"10.48550/arxiv.2204.14198","metadata_source":"pith","pith_arxiv_id":"2204.14198","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Flamingo: a Visual Language Model for Few-Shot Learning","venue":"cs.CV","work_id":"a110f764-38dc-41b2-a802-53744ecea1fc","year":2022},"citing_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-05-13T14:22:16.968028Z"},"links":{"cited_paper":"/paper/2204.14198","citing_paper":"/paper/2210.08402"},"observation_digest":"sha256:895abb9ea894a76377b3a1003627f365a431681735ad256dc2790c91a1802c6b","observation_id":"d68a3a7f-7a8e-4d40-8baa-1530aabb2bab","resolution":{"observed_at":"2026-05-13T14:22:17.143757Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Objectnet: A large-scale bias-controlled dataset for pushing the limits of object recognition models","venue":null,"work_id":"ad3694db-c8ca-468d-942d-9c6318accd35","year":2019},"citing_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-05-13T14:22:16.968028Z"},"links":{"citing_paper":"/paper/2210.08402"},"observation_digest":"sha256:46e5e833436ba75ebaada6cb7d072cf7f9a5cb42d10d547e45a9764871ed6178","observation_id":"d9afbb43-61e9-4cdc-8932-6ace7b9e14e7","resolution":{"observed_at":"2026-05-13T14:22:17.689179Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Bender, Timnit Gebru, Angelina McMillan-Major, and Shmargaret Shmitchell","venue":null,"work_id":"c052de4b-03e8-406e-8d28-230442514730","year":2021},"citing_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-05-13T14:22:16.968028Z"},"links":{"citing_paper":"/paper/2210.08402"},"observation_digest":"sha256:efc8b287987378f9f9711ccf4bcd41e3d41825b6ee59729e49243f0e7a667eb8","observation_id":"84bfd6d1-54a7-47f1-b139-b9bc2a7300c9","resolution":{"observed_at":"2026-05-13T14:22:17.567980Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Large image datasets: A pyrrhic win for computer vision? InProceedings of IEEE Winter Conference on Applications of Computer Vision (WACV), pages 1536–1546","venue":null,"work_id":"9696afdd-3bca-4794-9bfd-277800a26cbb","year":2021},"citing_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-05-13T14:22:16.968028Z"},"links":{"citing_paper":"/paper/2210.08402"},"observation_digest":"sha256:93cf73059f340a3cca83163581ef77577e7265d764c2e2fb4d1f7be4dd7975da","observation_id":"f20d21e1-0687-4ae5-b225-c42ccb86aabf","resolution":{"observed_at":"2026-05-13T14:22:17.513740Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Multimodaldatasets: misogyny, pornography, and malignant stereotypes","venue":null,"work_id":"90739145-bccd-4020-bc90-d55deb4fcebd","year":2021},"citing_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-05-13T14:22:16.968028Z"},"links":{"citing_paper":"/paper/2210.08402"},"observation_digest":"sha256:143343e13253ab1e5a0308cf6b45e57e584dc5e277e93af090a373b6be29fa91","observation_id":"0758d398-0802-448c-8e4e-0075ca4b438a","resolution":{"observed_at":"2026-05-13T14:22:17.720819Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Food-101–mining discriminative components with random forests","venue":null,"work_id":"c2b9b38d-07f6-4b32-87df-75680d33e45c","year":2014},"citing_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-05-13T14:22:16.968028Z"},"links":{"citing_paper":"/paper/2210.08402"},"observation_digest":"sha256:92e8691c7f36f724453e24f9e00a911f9e4c7d65a1548fe5fee4d143fc270a1d","observation_id":"6fde7f0c-dceb-4d73-ab8a-6b85f0beb8c3","resolution":{"observed_at":"2026-05-13T14:22:17.657639Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-09T14:26:21.117928Z","title":"Language models are few-shot learners","venue":null,"work_id":"04bc68bc-b7df-4ec1-8599-da037bd4f085","year":1901},"citing_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-05-13T14:22:16.968028Z"},"links":{"citing_paper":"/paper/2210.08402"},"observation_digest":"sha256:824238e182c61a46adb7813a594dd4f875b090173a7bd42e42af264cc62d1214","observation_id":"f59160fe-0b74-4412-bdfb-bc99276515b2","resolution":{"observed_at":"2026-05-13T14:22:17.767853Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2005.14165","last_updated":"2020-07-22T19:47:17Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2020-05-28T17:29:03Z","title":"Language Models are Few-Shot Learners","version":4},"cited_work":{"arxiv_id":"2005.14165","doi":"10.1145/1926385.1926423","metadata_source":"pith","pith_arxiv_id":"2005.14165","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Language Models are Few-Shot Learners","venue":"cs.CL","work_id":"214732c0-2edd-44a0-af9e-28184a2b8279","year":2020},"citing_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-05-13T14:22:16.968028Z"},"links":{"cited_paper":"/paper/2005.14165","citing_paper":"/paper/2210.08402"},"observation_digest":"sha256:52c4e27d362b3a8199da84a24cfade51296d274ab3ad953173d9b217326df448","observation_id":"73890cc8-2891-427f-910f-a5bf5c6d3630","resolution":{"observed_at":"2026-05-13T14:22:17.167292Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-07-09T08:48:33.42086+00:00","source":"crossref_status_cache"},{"observed_at":"2026-07-09T08:48:33.42086+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Cross-lingual and multilingual clip","venue":null,"work_id":"7dc52a56-6ea9-4cfe-a601-f3dae3650b21","year":2022},"citing_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-05-13T14:22:16.968028Z"},"links":{"citing_paper":"/paper/2210.08402"},"observation_digest":"sha256:8142ed8629ec1d73335bab9aa55f70e95cb7d688d540eca504d62d8d0ec33711","observation_id":"04fd5cc3-e4a4-436e-aa81-1224b848443d","resolution":{"observed_at":"2026-05-13T14:22:17.746743Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Conceptual 12m: Pushing web-scale image-text pre-training to recognize long-tail visual concepts","venue":null,"work_id":"20bd287a-2b8c-405f-a9d1-b93a901b08fe","year":2021},"citing_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-05-13T14:22:16.968028Z"},"links":{"citing_paper":"/paper/2210.08402"},"observation_digest":"sha256:ef48733b2716a13224f36c820a75d29d9ffe67376d1781d38d1bd8d5f5aa46aa","observation_id":"977f92ad-a6fe-4d92-8af4-e8dcf258ff22","resolution":{"observed_at":"2026-05-13T14:22:17.684639Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1311.3618","last_updated":"2013-11-15T16:14:12Z","snapshot_observed_at":"2026-08-15T14:49:17.072467Z","submitted_at":"2013-11-14T19:28:35Z","title":"Describing Textures in the Wild","version":2},"cited_work":{"arxiv_id":"1311.3618","doi":null,"metadata_source":"pith","pith_arxiv_id":"1311.3618","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Describing Textures in the Wild","venue":"cs.CV","work_id":"2c321446-999a-4f13-b21c-a2f238ec189d","year":2013},"citing_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-05-13T14:22:16.968028Z"},"links":{"cited_paper":"/paper/1311.3618","citing_paper":"/paper/2210.08402"},"observation_digest":"sha256:a08b33b227800f276100e74b1494d80bac0112088d26f4f1c7cf183d7550f8f9","observation_id":"49b5559a-a828-487c-a666-12a4407f1e5f","resolution":{"observed_at":"2026-05-13T14:22:17.175514Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-09T06:36:03.268346Z","title":"Imagenet: A large- scale hierarchical image database","venue":null,"work_id":"6ee29c54-0013-4f3e-8bcb-5c870412e0cb","year":2009},"citing_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-05-13T14:22:16.968028Z"},"links":{"citing_paper":"/paper/2210.08402"},"observation_digest":"sha256:5a92f134b1b1b7137d48da82f3a7f97a691559b138f2d70f8546cb4fe79af7fb","observation_id":"2a98c442-0915-4051-a7e0-1c90267fb4e0","resolution":{"observed_at":"2026-05-13T14:22:17.705959Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2111.11431","last_updated":"2021-11-22T18:59:34Z","snapshot_observed_at":"2026-08-16T17:40:07.777206Z","submitted_at":"2021-11-22T18:59:34Z","title":"RedCaps: web-curated image-text data created by the people, for the people","version":1},"cited_work":{"arxiv_id":"2111.11431","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2111.11431","snapshot_observed_at":"2026-07-03T03:57:38.902956Z","title":"Redcaps: Web-curated image-text data created by the people, for the people","venue":null,"work_id":"567bf895-e7af-4229-97b8-94ff08ba8f5c","year":2021},"citing_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-05-13T14:22:16.968028Z"},"links":{"cited_paper":"/paper/2111.11431","citing_paper":"/paper/2210.08402"},"observation_digest":"sha256:dd186e5a5d0956507875f2fe81773982ba65ba5d2b07fca5ad546cea0da3f52d","observation_id":"9883e51e-1aa4-4c83-b205-dc56eb6ee62e","resolution":{"observed_at":"2026-05-13T14:22:17.136475Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2010.11929","last_updated":"2021-06-03T13:08:56Z","snapshot_observed_at":"2026-08-16T09:25:53.087782Z","submitted_at":"2020-10-22T17:55:59Z","title":"An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale","version":2},"cited_work":{"arxiv_id":"2010.11929","doi":"10.1175/jcli-d-22-0357.1","metadata_source":"pith","pith_arxiv_id":"2010.11929","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale","venue":"cs.CV","work_id":"e96730e3-129b-4db6-b981-15ab7932e297","year":2020},"citing_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-05-13T14:22:16.968028Z"},"links":{"cited_paper":"/paper/2010.11929","citing_paper":"/paper/2210.08402"},"observation_digest":"sha256:1f79f380bf45d4f1fa483b0e7414e67cddde8d4ac54c2b78da3dfd0c0653c41d","observation_id":"ee4dfd04-7169-4111-ad8c-0b0857b8b7d8","resolution":{"observed_at":"2026-05-13T14:22:17.184028Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2112.05253","last_updated":"2022-10-24T21:35:42Z","snapshot_observed_at":"2026-08-19T16:14:33.749505Z","submitted_at":"2021-12-09T23:58:45Z","title":"MAGMA -- Multimodal Augmentation of Generative Models through Adapter-based Finetuning","version":2},"cited_work":{"arxiv_id":"2112.05253","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2112.05253","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"arXiv preprint arXiv:2112.05253 , eprint =","venue":null,"work_id":"9707198b-280e-43c9-81bd-675e68a13ebc","year":2021},"citing_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-05-13T14:22:16.968028Z"},"links":{"cited_paper":"/paper/2112.05253","citing_paper":"/paper/2210.08402"},"observation_digest":"sha256:43aa131a4205703b3470f8e1e815902acadc61deb92819aa5b27fc1da89e9c7e","observation_id":"50c783e0-9192-44ba-a618-f75dd5eebee0","resolution":{"observed_at":"2026-05-13T14:22:17.193463Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"CLIP on wheels: Zero-shot object navigation as object localization and exploration","venue":null,"work_id":"04eed7af-d79b-4410-b260-eca42a1f6d1a","year":2022},"citing_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-05-13T14:22:16.968028Z"},"links":{"citing_paper":"/paper/2210.08402"},"observation_digest":"sha256:9fccd0c47ff756c5d9764a1b74ec21692c2e132688e9e6a1b08e588459ae8f5e","observation_id":"62120ce5-2ff9-4bf1-84fd-5235da044291","resolution":{"observed_at":"2026-05-13T14:22:17.725331Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2101.00027","last_updated":"2020-12-31T19:00:10Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2020-12-31T19:00:10Z","title":"The Pile: An 800GB Dataset of Diverse Text for Language Modeling","version":1},"cited_work":{"arxiv_id":"2101.00027","doi":"10.1117/1.jmi.10.6.061104","metadata_source":"pith","pith_arxiv_id":"2101.00027","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"The Pile: An 800GB Dataset of Diverse Text for Language Modeling","venue":"cs.CL","work_id":"9b10667a-da61-4358-aceb-10578234d45d","year":2020},"citing_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-05-13T14:22:16.968028Z"},"links":{"cited_paper":"/paper/2101.00027","citing_paper":"/paper/2210.08402"},"observation_digest":"sha256:e5ddfab92756dbea0cb6df89685c0e881d0c20b11d23499b5543ddc6f2396e35","observation_id":"db113981-9639-4705-aa81-278f89bcedb9","resolution":{"observed_at":"2026-05-13T14:22:17.202625Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2204.14095","last_updated":"2022-05-28T08:52:58Z","snapshot_observed_at":"2026-08-18T15:46:27.104396Z","submitted_at":"2022-04-29T13:38:42Z","title":"PyramidCLIP: Hierarchical Feature Alignment for Vision-language Model Pretraining","version":2},"cited_work":{"arxiv_id":"2204.14095","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2204.14095","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Pyramidclip: Hierarchical feature alignment for vision-language model pretraining","venue":null,"work_id":"dc534238-fd44-4074-b739-836666c0436d","year":2022},"citing_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-05-13T14:22:16.968028Z"},"links":{"cited_paper":"/paper/2204.14095","citing_paper":"/paper/2210.08402"},"observation_digest":"sha256:5bf35b15d85cca4921802c751cfe9bb2c9bad20eacd63c1105eac4af2b7291df","observation_id":"b135d550-b885-4e7d-aa7c-41e083e44ffd","resolution":{"observed_at":"2026-05-13T14:22:17.209492Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Just: Large-scale multi-tier storage infrastructure at the jülich supercomputing centre","venue":null,"work_id":"9c7ce97f-e867-40e4-badf-06a1c4c148a8","year":2021},"citing_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-05-13T14:22:16.968028Z"},"links":{"citing_paper":"/paper/2210.08402"},"observation_digest":"sha256:37d64ea9fc1602a15d15770d975acb40b069ba8488c40d3de0c7360ef02b6bad","observation_id":"dd954bc3-f101-4e76-bf35-0cd01c07adaa","resolution":{"observed_at":"2026-05-13T14:22:17.737928Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2111.14822","last_updated":"2022-03-03T10:49:30Z","snapshot_observed_at":"2026-08-18T22:17:36.489843Z","submitted_at":"2021-11-29T18:59:46Z","title":"Vector Quantized Diffusion Model for Text-to-Image Synthesis","version":3},"cited_work":{"arxiv_id":"2111.14822","doi":"10.48550/arxiv.2111.14822","metadata_source":"arxiv_reference","pith_arxiv_id":"2111.14822","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Vector quantized diffusion model for text-to-image synthesis","venue":"arXiv (Cornell University)","work_id":"74abb574-5815-4cf3-8ccb-c2cacd465abd","year":2022},"citing_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-05-13T14:22:16.968028Z"},"links":{"cited_paper":"/paper/2111.14822","citing_paper":"/paper/2210.08402"},"observation_digest":"sha256:350a04b753f61e6e5253c85857ff46f6f8c833616de9bb006ce5c1846094bed0","observation_id":"2639c8cc-aa86-4cdb-9214-55ba8781bf43","resolution":{"observed_at":"2026-05-13T14:22:17.217234Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2016.17216","doi":"10.1001/jama.2016.17216","metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Stumpe, Derek Wu, Arunachalam Narayanaswamy, Subhashini Venugopalan, Kasumi Widner, Tom Madams, Jorge Cuadros, Ramasamy Kim, Rajiv Raman, Philip C","venue":"JAMA","work_id":"85791795-be73-4fe8-873c-f5b618f9678a","year":2016},"citing_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-05-13T14:22:16.968028Z"},"links":{"citing_paper":"/paper/2210.08402"},"observation_digest":"sha256:3764b6875390fb9956bbbb4160bc6bb030f721ecd8e84edaf4266473b4e9adfd","observation_id":"c32dfee0-a0ac-4798-b943-9309a27e2dd8","resolution":{"observed_at":"2026-05-13T14:22:17.103688Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-05-23T05:53:05.53995+00:00","source":"crossref_status_cache"},{"observed_at":"2026-05-23T05:53:05.53995+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"The many faces of robustness: A critical analysis of out-of-distribution generalization","venue":null,"work_id":"1b96f4a7-ea61-42e8-aa66-f075fce9313e","year":2021},"citing_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-05-13T14:22:16.968028Z"},"links":{"citing_paper":"/paper/2210.08402"},"observation_digest":"sha256:46c45fd60ac25d6ea26ba5305519aca510af335a6ab3130c7a6ac28007fe5dc6","observation_id":"46bb2bbe-b152-407c-9ddc-6a9df46af14f","resolution":{"observed_at":"2026-05-13T14:22:17.751121Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Natural adversarial examples","venue":null,"work_id":"5d0aa8cb-6c22-480a-9c74-3296e515a7cd","year":2021},"citing_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-05-13T14:22:16.968028Z"},"links":{"citing_paper":"/paper/2210.08402"},"observation_digest":"sha256:4b021418c0b7ea0b0f5f7fbe2c452f082cdcc6fe9dff74c6d2919121a5e610b0","observation_id":"bc4bed24-fd2b-4d4e-bf15-670d4ab9e1f1","resolution":{"observed_at":"2026-05-13T14:22:17.754996Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1907.07174","last_updated":"2021-03-04T21:56:19Z","snapshot_observed_at":"2026-08-20T17:03:26.723738Z","submitted_at":"2019-07-16T17:56:30Z","title":"Natural Adversarial Examples","version":4},"cited_work":{"arxiv_id":"1907.07174","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"1907.07174","snapshot_observed_at":"2026-06-30T13:04:40.412664Z","title":"arXiv preprint arXiv:1907.07174 , Title =","venue":null,"work_id":"d53b74a0-9138-43bf-b402-c3e707ee3eca","year":1907},"citing_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-05-13T14:22:16.968028Z"},"links":{"cited_paper":"/paper/1907.07174","citing_paper":"/paper/2210.08402"},"observation_digest":"sha256:987fb2b1a2bfa95c2b80bfcf528d070523c6ee08bbe6265f0302db06fd6e2139","observation_id":"e27049b8-84ce-4bf0-9cb9-5344cf53bf4c","resolution":{"observed_at":"2026-05-13T14:22:17.226412Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2111.12233","last_updated":"2022-03-26T02:02:42Z","snapshot_observed_at":"2026-08-16T17:39:46.069553Z","submitted_at":"2021-11-24T02:30:22Z","title":"Scaling Up Vision-Language Pre-training for Image Captioning","version":2},"cited_work":{"arxiv_id":"2111.12233","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2111.12233","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Scaling up vision-language pre-training for image captioning.arXiv preprint arXiv:2111.12233, 2021a","venue":null,"work_id":"b2b2c3b7-8b5d-48dc-b289-7edf4d39ff9a","year":2021},"citing_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-05-13T14:22:16.968028Z"},"links":{"cited_paper":"/paper/2111.12233","citing_paper":"/paper/2210.08402"},"observation_digest":"sha256:b721decde94fe737442089f04fc1c0ecf78ce5fdacb730d349246d1679bc78bb","observation_id":"8ba3aa5b-d7dd-4656-97e5-249449d7553c","resolution":{"observed_at":"2026-05-13T14:22:17.233419Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.5281/ze","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Openclip, July 2021","venue":"LA Referencia (Red Federada de Repositorios Institucionales de Publicaciones Científicas)","work_id":"3261e18c-11ec-49b1-a701-54daf9fca0fe","year":2026},"citing_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-05-13T14:22:16.968028Z"},"links":{"citing_paper":"/paper/2210.08402"},"observation_digest":"sha256:618e44b6b5efb76fb601877790bd7b53c2059bd658da327790d7c4c2f5e0a44e","observation_id":"b3cc8200-00d3-4239-96da-96381479b2a6","resolution":{"observed_at":"2026-05-13T14:22:17.086135Z","resolver_source":"doi_truncated","status":"malformed_identifier"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2102.05918","last_updated":"2021-06-11T07:51:39Z","snapshot_observed_at":"2026-08-20T11:12:15.738367Z","submitted_at":"2021-02-11T10:08:12Z","title":"Scaling Up Visual and Vision-Language Representation Learning With Noisy Text Supervision","version":2},"cited_work":{"arxiv_id":"2102.05918","doi":"10.48550/arxiv.2102.05918","metadata_source":"arxiv_reference","pith_arxiv_id":"2102.05918","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Le, Yunhsuan Sung, Zhen Li, and Tom Duerig","venue":"arXiv (Cornell University)","work_id":"d28390f3-8b21-4b2a-a523-473a16c2e43a","year":2021},"citing_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-05-13T14:22:16.968028Z"},"links":{"cited_paper":"/paper/2102.05918","citing_paper":"/paper/2210.08402"},"observation_digest":"sha256:00489dbf8913471cc4cb394bf373e6d356c18355c6fb45bd018c7984b5740800","observation_id":"f0e83b57-fdfe-46bf-9ec6-98f03ef143af","resolution":{"observed_at":"2026-05-13T14:22:17.247569Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"JUWELS Booster Supercomputer, 2020.https://apps.fz- juelich.de/jsc/hps/juwels/configuration.html#hardware-configuration-of-the-sys tem-name-booster-module","venue":null,"work_id":"26803266-bbb6-4077-b63a-4247d4542eb1","year":2020},"citing_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-05-13T14:22:16.968028Z"},"links":{"citing_paper":"/paper/2210.08402"},"observation_digest":"sha256:39ebe5a77bf0c12d9d18b02e1f9d1dbacce6ff48bc1222a5cc1be786a5465ef0","observation_id":"6f7d42ea-f004-4c06-a7c5-4950312dedc6","resolution":{"observed_at":"2026-05-13T14:22:17.775979Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2001.08361","last_updated":"2020-01-23T03:59:20Z","snapshot_observed_at":"2026-08-13T17:41:53.092611Z","submitted_at":"2020-01-23T03:59:20Z","title":"Scaling Laws for Neural Language Models","version":1},"cited_work":{"arxiv_id":"2001.08361","doi":"10.1145/3616855.3635845","metadata_source":"pith","pith_arxiv_id":"2001.08361","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Scaling Laws for Neural Language Models","venue":"cs.LG","work_id":"b7dd8749-9c45-4977-ab9b-64478dce1ae8","year":2020},"citing_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-05-13T14:22:16.968028Z"},"links":{"cited_paper":"/paper/2001.08361","citing_paper":"/paper/2210.08402"},"observation_digest":"sha256:4d18f14cd050f32be29968ab219f717790fd08645e850ce1208b40fb9b0c5599","observation_id":"e7eda4a6-ee56-4ccd-b6fe-96f04e655ec8","resolution":{"observed_at":"2026-05-13T14:22:17.253829Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Deep visual-semantic alignments for generating image descrip- tions","venue":null,"work_id":"01e6c944-e038-4331-8de6-998c4223ed80","year":2015},"citing_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-05-13T14:22:16.968028Z"},"links":{"citing_paper":"/paper/2210.08402"},"observation_digest":"sha256:7095102f2df5b05f0562e43e0948314a4ffb7de5337f5f177f371094e4d02841","observation_id":"351f10ba-a9ca-46b0-a8c4-49250cf01010","resolution":{"observed_at":"2026-05-13T14:22:17.786264Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2111.09888","last_updated":"2022-04-15T02:12:26Z","snapshot_observed_at":"2026-08-19T14:00:02.361874Z","submitted_at":"2021-11-18T18:59:59Z","title":"Simple but Effective: CLIP Embeddings for Embodied AI","version":2},"cited_work":{"arxiv_id":"2111.09888","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2111.09888","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Khandelwal, L","venue":null,"work_id":"9f506190-99d1-4f2e-812c-45586b3eb115","year":2021},"citing_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-05-13T14:22:16.968028Z"},"links":{"cited_paper":"/paper/2111.09888","citing_paper":"/paper/2210.08402"},"observation_digest":"sha256:17f153a50dd810b5fdf54e863f8a9e0f115fc2c37c6b523c4d5f5a0a9ea9b1f0","observation_id":"bd4c3176-4c99-4d22-b325-8bde8af620d9","resolution":{"observed_at":"2026-05-13T14:22:17.259795Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Big transfer (bit): General visual representation learning","venue":null,"work_id":"90fbdf0d-939b-403b-abbb-8af711ab9ee1","year":2020},"citing_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-05-13T14:22:16.968028Z"},"links":{"citing_paper":"/paper/2210.08402"},"observation_digest":"sha256:f9fc111cafa340f34549a0371ea1e2a62e847d18b7ba26bff5b5452eaf1c8151","observation_id":"075513e8-ceb5-4fb2-a30e-ed8e6b18b91a","resolution":{"observed_at":"2026-05-13T14:22:17.803874Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1805.08974","last_updated":"2019-06-17T16:25:07Z","snapshot_observed_at":"2026-08-14T19:12:11.424350Z","submitted_at":"2018-05-23T06:12:35Z","title":"Do Better ImageNet Models Transfer Better?","version":3},"cited_work":{"arxiv_id":"1805.08974","doi":null,"metadata_source":"pith","pith_arxiv_id":"1805.08974","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Do Better ImageNet Models Transfer Better?","venue":"cs.CV","work_id":"74b42758-70c6-49e6-b315-fd6432682d0b","year":2018},"citing_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-05-13T14:22:16.968028Z"},"links":{"cited_paper":"/paper/1805.08974","citing_paper":"/paper/2210.08402"},"observation_digest":"sha256:6aa13f5d8bf42d5576740ad91a5503b2fe6c4a99e0edef83928977981daa8960","observation_id":"5c3bdd48-021d-4911-adfa-0010a800d04c","resolution":{"observed_at":"2026-05-13T14:22:17.266624Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"3d object representations for ﬁne- grained categorization","venue":null,"work_id":"255e3e20-41c1-422e-8a7a-0851016d83dc","year":null},"citing_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-05-13T14:22:16.968028Z"},"links":{"citing_paper":"/paper/2210.08402"},"observation_digest":"sha256:90364fbf7d2d6077ec15b8cef69e0fc421677e0fcefc861004cc9541ba78f37f","observation_id":"fc02bfc5-7080-42e0-87ab-b23bf382df65","resolution":{"observed_at":"2026-05-13T14:22:17.817213Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"document/6755945","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"3D Object Representations for Fine-Grained Categorization","venue":null,"work_id":"cbe183d7-78b7-4102-b41f-e83b491d6e87","year":2013},"citing_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-05-13T14:22:16.968028Z"},"links":{"citing_paper":"/paper/2210.08402"},"observation_digest":"sha256:3c39c96f3593503423a78df3d0beca984045a1ee294670f6265e4e8e8bb454ba","observation_id":"a3dc6e01-f26c-41e8-904c-9651b9a60932","resolution":{"observed_at":"2026-05-13T14:22:17.272263Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Visual genome: Connecting language and vision using crowdsourced dense image annotations.International journal of computer vision, 123(1):32–73","venue":null,"work_id":"0c60ee3f-b97f-492e-ab68-76a5e6cc4423","year":2017},"citing_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-05-13T14:22:16.968028Z"},"links":{"citing_paper":"/paper/2210.08402"},"observation_digest":"sha256:6475d3f068247cab78cf7f29849dc057a4b851366c3b7f555a3596234e615637","observation_id":"77c7f31f-3daf-4a54-a2ff-d46a406e9714","resolution":{"observed_at":"2026-05-13T14:22:17.826509Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Learning multiple layers of features from tiny images","venue":null,"work_id":"774971ce-a874-4d94-a61f-a25253d589b5","year":null},"citing_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-05-13T14:22:16.968028Z"},"links":{"citing_paper":"/paper/2210.08402"},"observation_digest":"sha256:c7a8bf75ecea2530a010bed88d63329ac7deab97563ff2a21658a9b3839a0453","observation_id":"3bf90083-396a-4e75-86e0-8bfb75036b68","resolution":{"observed_at":"2026-05-13T14:22:17.830512Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":null,"venue":null,"work_id":"89b8e932-2bc5-4205-8a1c-fc384b1cb5ad","year":2009},"citing_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-05-13T14:22:16.968028Z"},"links":{"citing_paper":"/paper/2210.08402"},"observation_digest":"sha256:9be80dd94fbe6a49a8498af856e498859e256b223595b249e5113ac9c676aa21","observation_id":"93313354-edc0-40b6-9134-6a1ca1674e7e","resolution":{"observed_at":"2026-05-13T14:22:17.834170Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2205.06397","last_updated":"2022-05-12T23:37:29Z","snapshot_observed_at":"2026-08-16T17:00:38.555763Z","submitted_at":"2022-05-12T23:37:29Z","title":"LANTERN-RD: Enabling Deep Learning for Mitigation of the Invasive Spotted Lanternfly","version":1},"cited_work":{"arxiv_id":"2205.06397","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2205.06397","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Lantern-rd: Enabling deep learning for mitigation of the invasive spotted lanternﬂy","venue":null,"work_id":"6709c5b3-5a0a-4e10-bc79-6bcd1f5a06fd","year":2022},"citing_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-05-13T14:22:16.968028Z"},"links":{"cited_paper":"/paper/2205.06397","citing_paper":"/paper/2210.08402"},"observation_digest":"sha256:4766c7781f140ab96d5c795c183a967ab9a8ebf1849f2ba0ff4318c148f03ba2","observation_id":"c06b7ab3-46f1-41cb-b9b3-9b875fce4bca","resolution":{"observed_at":"2026-05-13T14:22:17.278762Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"The open images dataset v4: Uniﬁed image classiﬁcation, object detection, and visual relationship detection at scale.IJCV","venue":null,"work_id":"062c30a6-7289-46a7-ae0d-2e80f534a128","year":2020},"citing_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-05-13T14:22:16.968028Z"},"links":{"citing_paper":"/paper/2210.08402"},"observation_digest":"sha256:179cd19df4a3a145884974d4ab8630857724b0cd8de386340f4897468ddfd3cd","observation_id":"c247f732-531f-462d-b06d-799594784d17","resolution":{"observed_at":"2026-05-13T14:22:17.843093Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"The bigscience roots corpus: A 1.6 tb composite multilingual dataset","venue":null,"work_id":"7b0eeec7-2710-4e6a-a2d9-a402a73663a4","year":null},"citing_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-05-13T14:22:16.968028Z"},"links":{"citing_paper":"/paper/2210.08402"},"observation_digest":"sha256:d16d1dd48da3def6e1b63c379f7ab43cb4f87e2f15a54e89f299a19d4a2d5904","observation_id":"96240345-3d7c-40eb-b3cd-58505ce374ed","resolution":{"observed_at":"2026-05-13T14:22:17.850915Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Learning visual n-grams from web data","venue":null,"work_id":"b847623d-8de2-4b1f-9c6c-eb9211280af2","year":2017},"citing_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-05-13T14:22:16.968028Z"},"links":{"citing_paper":"/paper/2210.08402"},"observation_digest":"sha256:41a42f0705a619bd05cfb2a52782d2601ce6ddbb362775065de989974b41f54f","observation_id":"377b89df-247a-4d3d-8eb8-47b7f3499404","resolution":{"observed_at":"2026-05-13T14:22:17.858684Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2201.12086","last_updated":"2022-02-15T05:43:32Z","snapshot_observed_at":"2026-08-20T06:46:31.583175Z","submitted_at":"2022-01-28T12:49:48Z","title":"BLIP: Bootstrapping Language-Image Pre-training for Unified Vision-Language Understanding and Generation","version":2},"cited_work":{"arxiv_id":"2201.12086","doi":"10.48550/arxiv.2201.12086","metadata_source":"pith","pith_arxiv_id":"2201.12086","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Blip: Bootstrapping language- image pre-training for uniﬁed vision-language understanding and generation","venue":"cs.CV","work_id":"ed5a5938-1f3b-44a9-9543-ebafa9af4d53","year":2022},"citing_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-05-13T14:22:16.968028Z"},"links":{"cited_paper":"/paper/2201.12086","citing_paper":"/paper/2210.08402"},"observation_digest":"sha256:49ecf08b029647473f61bd150ba97e607d0555fa133c16540d743d5c1c79bfc3","observation_id":"593de29b-f42b-43f9-a565-bfa484b3952f","resolution":{"observed_at":"2026-05-13T14:22:17.291001Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-09T07:06:04.222209Z","title":"Microsoft coco: Common objects in context","venue":null,"work_id":"a8f99b11-d80b-4475-8f1d-9eab347a2b21","year":2014},"citing_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-05-13T14:22:16.968028Z"},"links":{"citing_paper":"/paper/2210.08402"},"observation_digest":"sha256:13edc952ab5d32b99614ac9f9e8fe969320fbbc22bfef7c9c935e6cf33234ad9","observation_id":"92a1f2c6-a5eb-44c4-bcad-dc6b8543980f","resolution":{"observed_at":"2026-05-13T14:22:17.486143Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2202.09778","last_updated":"2022-10-31T09:05:25Z","snapshot_observed_at":"2026-08-16T17:20:02.890207Z","submitted_at":"2022-02-20T10:37:52Z","title":"Pseudo Numerical Methods for Diffusion Models on Manifolds","version":2},"cited_work":{"arxiv_id":"2202.09778","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2202.09778","snapshot_observed_at":"2026-07-02T16:37:09.182860Z","title":"Pseudo numerical methods for diffusion models on manifolds","venue":null,"work_id":"a381acd0-117e-4e82-8d12-5ebd800fc382","year":2022},"citing_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-05-13T14:22:16.968028Z"},"links":{"cited_paper":"/paper/2202.09778","citing_paper":"/paper/2210.08402"},"observation_digest":"sha256:0b5532d27d128fe80476ed9c97833d9d20510393eacc41b3054a48abb086dc70","observation_id":"f25176e3-5c14-4cf6-adec-6584fc2053aa","resolution":{"observed_at":"2026-05-13T14:22:17.297830Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Exploring the limits of weakly supervised pretraining","venue":null,"work_id":"3fb96272-4cac-412a-8e7a-54948409cd58","year":2018},"citing_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-05-13T14:22:16.968028Z"},"links":{"citing_paper":"/paper/2210.08402"},"observation_digest":"sha256:8579374b4845a579ae85f95d5fb1ab9f25f925723639e63854f13e40e76082fa","observation_id":"7c6adbe7-fdf4-44d1-8adf-2345bbeac63f","resolution":{"observed_at":"2026-05-13T14:22:17.501656Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1511.02793","last_updated":"2016-02-29T17:56:29Z","snapshot_observed_at":"2026-08-22T01:20:29.168233Z","submitted_at":"2015-11-09T18:18:53Z","title":"Generating Images from Captions with Attention","version":2},"cited_work":{"arxiv_id":"1511.02793","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"1511.02793","snapshot_observed_at":"2026-07-04T20:51:55.048399Z","title":"Generating images from captions with attention","venue":null,"work_id":"85a2d4eb-27a5-4c05-a716-f0d647b25f7c","year":2015},"citing_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-05-13T14:22:16.968028Z"},"links":{"cited_paper":"/paper/1511.02793","citing_paper":"/paper/2210.08402"},"observation_digest":"sha256:0dd3ea096da5ea6daf27ceffb068250dc48a70c5f2efd9b2ad2c2cec8a0a9c7a","observation_id":"7f0a1c13-f039-4800-b50e-c4ee381e43cb","resolution":{"observed_at":"2026-07-04T20:51:55.048399Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Ciagan: Conditional identity anonymiza- tion generative adversarial networks","venue":null,"work_id":"377e0326-11c8-4d3a-a1cb-181a0f1e8f72","year":2020},"citing_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-05-13T14:22:16.968028Z"},"links":{"citing_paper":"/paper/2210.08402"},"observation_digest":"sha256:df541fbc12073d8bb07b1709f15586d606b854de8a2c893ba63c1a110898ee9d","observation_id":"4c07b8d1-870d-44c7-a42e-9d0eabadbbdf","resolution":{"observed_at":"2026-05-13T14:22:17.523416Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Model cards for model reporting","venue":null,"work_id":"bec1740f-5d4b-40f0-bc99-37717f335d16","year":2019},"citing_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-05-13T14:22:16.968028Z"},"links":{"citing_paper":"/paper/2210.08402"},"observation_digest":"sha256:c18c6924f3b080790d97cb13f565e1f72475b8df17d136262b2425995656c5a7","observation_id":"28cf3391-89a0-4c0e-baed-8b155c0cfd50","resolution":{"observed_at":"2026-05-13T14:22:17.534000Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2111.09734","last_updated":"2021-11-18T14:49:15Z","snapshot_observed_at":"2026-08-16T17:40:54.088104Z","submitted_at":"2021-11-18T14:49:15Z","title":"ClipCap: CLIP Prefix for Image Captioning","version":1},"cited_work":{"arxiv_id":"2111.09734","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2111.09734","snapshot_observed_at":"2026-07-04T10:09:44.426723Z","title":"arXiv preprint arXiv: 2111.09734 (2021)","venue":null,"work_id":"6cf76e0a-4411-443c-b127-57f0f3574f41","year":2021},"citing_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-05-13T14:22:16.968028Z"},"links":{"cited_paper":"/paper/2111.09734","citing_paper":"/paper/2210.08402"},"observation_digest":"sha256:0cb64886184276fa612c4c072070d48e3e17eb156e1561d30d1deb63a17ef149","observation_id":"7f11e737-20da-46c7-9a1c-c8852ac93363","resolution":{"observed_at":"2026-05-13T14:22:17.333000Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Image-to-word transformation based on dividing and vector quantizing images with words","venue":null,"work_id":"b9f37df5-9588-49d6-b31c-f77e1a3c49d1","year":1999},"citing_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"reference_index":53,"source":"pdf_text","source_observed_at":"2026-05-13T14:22:16.968028Z"},"links":{"citing_paper":"/paper/2210.08402"},"observation_digest":"sha256:88f7ffc76c9c8f5446947ac22910f41d4f62edad2b29c708d1152f66a055d3a0","observation_id":"ba7d5c4d-b1bf-432d-ad8e-43654c0f65b0","resolution":{"observed_at":"2026-05-13T14:22:17.548554Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2112.10741","last_updated":"2022-03-08T18:18:49Z","snapshot_observed_at":"2026-08-07T12:21:17.790675Z","submitted_at":"2021-12-20T18:42:55Z","title":"GLIDE: Towards Photorealistic Image Generation and Editing with Text-Guided Diffusion Models","version":3},"cited_work":{"arxiv_id":"2112.10741","doi":"10.48550/arxiv.2112.10741","metadata_source":"pith","pith_arxiv_id":"2112.10741","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"GLIDE: Towards Photorealistic Image Generation and Editing with Text-Guided Diffusion Models","venue":"cs.CV","work_id":"34430d19-7919-48ce-88a5-17b3bfe2192e","year":2021},"citing_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"reference_index":54,"source":"pdf_text","source_observed_at":"2026-05-13T14:22:16.968028Z"},"links":{"cited_paper":"/paper/2112.10741","citing_paper":"/paper/2210.08402"},"observation_digest":"sha256:80578abc06b83c9f1d46f82bbb8fde2287c39783f8c8032ce66aada74fa79730","observation_id":"6f5b3679-79c7-4b92-8bb6-b8cdaac00ff1","resolution":{"observed_at":"2026-05-13T14:22:17.338741Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-05-21T20:52:26.23702+00:00","source":"crossref_status_cache"},{"observed_at":"2026-05-21T20:52:26.23702+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"cld3: Google’s Compact Language Detector 3","venue":null,"work_id":"8b7fc959-1eeb-42aa-bef2-15f8af224abc","year":2022},"citing_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"reference_index":55,"source":"pdf_text","source_observed_at":"2026-05-13T14:22:16.968028Z"},"links":{"citing_paper":"/paper/2210.08402"},"observation_digest":"sha256:609057790cc09156dade60e137dc7ac5e86f75b7bb3e93a9de46606874adf0bc","observation_id":"f0100cd5-a32d-430a-a4f3-71203250066b","resolution":{"observed_at":"2026-05-13T14:22:17.560610Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2111.10050","last_updated":"2023-04-12T08:26:28Z","snapshot_observed_at":"2026-08-16T17:40:45.295399Z","submitted_at":"2021-11-19T05:25:46Z","title":"Combined Scaling for Zero-shot Transfer Learning","version":3},"cited_work":{"arxiv_id":"2111.10050","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2111.10050","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"arXiv preprint arXiv:2111.10050 , year=","venue":null,"work_id":"38fb2f70-f077-4765-8cb7-088bca890892","year":2021},"citing_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"reference_index":56,"source":"pdf_text","source_observed_at":"2026-05-13T14:22:16.968028Z"},"links":{"cited_paper":"/paper/2111.10050","citing_paper":"/paper/2210.08402"},"observation_digest":"sha256:f3c81f8809a4e789bf47b2a5ca0ce9984f1a76bc60ea02d8460fc0893f4d3f78","observation_id":"28196d98-8de3-471c-a22f-2ec5cd5c57da","resolution":{"observed_at":"2026-05-13T14:22:17.351271Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Connecting vision and language with localized narratives","venue":null,"work_id":"7a5dc5b8-de47-4c38-a534-8b3addc29b99","year":2020},"citing_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"reference_index":57,"source":"pdf_text","source_observed_at":"2026-05-13T14:22:16.968028Z"},"links":{"citing_paper":"/paper/2210.08402"},"observation_digest":"sha256:b65bf2fc82828d158e6ca69a103b708fa5d62a871f89f3703475550378a1ed1f","observation_id":"c93a8d30-1cae-47fa-bf39-b7076e693b2e","resolution":{"observed_at":"2026-05-13T14:22:17.571377Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Learning visual representations using images with captions","venue":null,"work_id":"b0f566e1-3c33-40ab-9c53-a206e5d16411","year":2007},"citing_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"reference_index":58,"source":"pdf_text","source_observed_at":"2026-05-13T14:22:16.968028Z"},"links":{"citing_paper":"/paper/2210.08402"},"observation_digest":"sha256:acb190ea952684a0b7a3eb70a5f461404da2ed3ccf8e3cd484f2473dcf4c1825","observation_id":"3753821e-a498-4616-bfe7-6711b04bc1f1","resolution":{"observed_at":"2026-05-13T14:22:17.575062Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2103.00020","last_updated":"2021-02-26T19:04:58Z","snapshot_observed_at":"2026-07-06T10:45:03.059688Z","submitted_at":"2021-02-26T19:04:58Z","title":"Learning Transferable Visual Models From Natural Language Supervision","version":1},"cited_work":{"arxiv_id":"2103.00020","doi":"10.1021/acs.jcim.0c00174","metadata_source":"pith","pith_arxiv_id":"2103.00020","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Learning Transferable Visual Models From Natural Language Supervision","venue":"cs.CV","work_id":"6de86bb5-27bd-4d5c-8b89-967ebfc52659","year":2021},"citing_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"reference_index":59,"source":"pdf_text","source_observed_at":"2026-05-13T14:22:16.968028Z"},"links":{"cited_paper":"/paper/2103.00020","citing_paper":"/paper/2210.08402"},"observation_digest":"sha256:455192beddbaafd4a5fefaa711fb43d650b524556dbb80bcd55f1599f0a23328","observation_id":"ca55c9cb-afb3-4525-b1ab-0b31d8976616","resolution":{"observed_at":"2026-05-13T14:22:17.364966Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-09T21:16:34.908673Z","title":"Learning transferable visual models from natural language supervision","venue":null,"work_id":"360ec4e7-4e16-4550-916f-fe5bcd5033bc","year":2021},"citing_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"reference_index":60,"source":"pdf_text","source_observed_at":"2026-05-13T14:22:16.968028Z"},"links":{"citing_paper":"/paper/2210.08402"},"observation_digest":"sha256:35fe2d85c78bfad3cb813e662d7f3ccd968f75f1ddd9b18526346c57862412d7","observation_id":"0ab6294b-f71d-4572-9ca8-f0a6e5b07464","resolution":{"observed_at":"2026-05-13T14:22:17.590634Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2102.12092","last_updated":"2021-02-26T23:26:05Z","snapshot_observed_at":"2026-07-06T10:44:09.403787Z","submitted_at":"2021-02-24T06:42:31Z","title":"Zero-Shot Text-to-Image Generation","version":2},"cited_work":{"arxiv_id":"2102.12092","doi":"10.48550/arxiv.2102.12092","metadata_source":"pith","pith_arxiv_id":"2102.12092","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Zero-Shot Text-to-Image Generation","venue":"cs.CV","work_id":"b687fcea-fa95-4504-9ab2-8a627cae0000","year":2021},"citing_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"reference_index":61,"source":"pdf_text","source_observed_at":"2026-05-13T14:22:16.968028Z"},"links":{"cited_paper":"/paper/2102.12092","citing_paper":"/paper/2210.08402"},"observation_digest":"sha256:1be121c341802f123c25524e191f94a106d8616eca2eb9920cb35e8c707bf81b","observation_id":"75ed9063-47eb-4890-a334-3c92310e7798","resolution":{"observed_at":"2026-05-13T22:26:09.277502Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Hierarchical text-conditional image generation with clip latents","venue":null,"work_id":"ee8863de-dcf4-40d6-93a0-294fe02ecb4a","year":2022},"citing_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"reference_index":62,"source":"pdf_text","source_observed_at":"2026-05-13T14:22:16.968028Z"},"links":{"citing_paper":"/paper/2210.08402"},"observation_digest":"sha256:9d5f53aa0d576178b12a2c3e2b350c8813eed50dedf04eb0e06d961a7d8bfc7f","observation_id":"5acb2e29-5d20-43e7-a2c8-99f61167b218","resolution":{"observed_at":"2026-05-13T14:22:17.605964Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Do ImageNet classiﬁers generalize to ImageNet? InInternational Conference on Machine Learning (ICML)","venue":null,"work_id":"055acd65-549b-42eb-ad28-756784238636","year":null},"citing_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"reference_index":63,"source":"pdf_text","source_observed_at":"2026-05-13T14:22:16.968028Z"},"links":{"citing_paper":"/paper/2210.08402"},"observation_digest":"sha256:615c1f6ea5cf48315fa5792b996d7c36bc2e678867e3f989e62c050066123e03","observation_id":"fedfcf40-1dd0-4357-9495-09013ca271d1","resolution":{"observed_at":"2026-05-13T14:22:17.619373Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1902.10811","last_updated":"2019-06-12T17:42:33Z","snapshot_observed_at":"2026-08-21T12:17:29.798015Z","submitted_at":"2019-02-13T20:35:44Z","title":"Do ImageNet Classifiers Generalize to ImageNet?","version":2},"cited_work":{"arxiv_id":"1902.10811","doi":"10.48550/arxiv.1902.10811","metadata_source":"pith","pith_arxiv_id":"1902.10811","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Do ImageNet Classifiers Generalize to ImageNet?","venue":"cs.CV","work_id":"4a7c0052-7cf8-4055-a2b8-0853668d673b","year":2019},"citing_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"reference_index":64,"source":"pdf_text","source_observed_at":"2026-05-13T14:22:16.968028Z"},"links":{"cited_paper":"/paper/1902.10811","citing_paper":"/paper/2210.08402"},"observation_digest":"sha256:4d1575c441ef25e00f8a574c8247b074079431834387ef16f3bf38699cc9adbd","observation_id":"0298e9fd-b984-4f6d-9ead-9b141fa8962f","resolution":{"observed_at":"2026-05-13T14:22:17.378251Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Generative adversarial text to image synthesis","venue":null,"work_id":"9929839e-c404-4993-a512-6d7b7e3a8fdd","year":2016},"citing_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"reference_index":65,"source":"pdf_text","source_observed_at":"2026-05-13T14:22:16.968028Z"},"links":{"citing_paper":"/paper/2210.08402"},"observation_digest":"sha256:c4da043fc9afc439fefeedb7fe0c9e5bb03938aedf75710c42cea59f8f779da5","observation_id":"0e3ee682-2494-4fe4-9448-36afa1a467b7","resolution":{"observed_at":"2026-05-13T14:22:17.637358Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2112.10752","last_updated":"2022-04-13T11:38:44Z","snapshot_observed_at":"2026-07-06T12:20:47.369918Z","submitted_at":"2021-12-20T18:55:25Z","title":"High-Resolution Image Synthesis with Latent Diffusion Models","version":2},"cited_work":{"arxiv_id":"2112.10752","doi":"10.48550/arxiv.2112.10752","metadata_source":"pith","pith_arxiv_id":"2112.10752","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"High-Resolution Image Synthesis with Latent Diffusion Models","venue":"cs.CV","work_id":"f0270d36-2952-47fb-84c1-95e3ec341126","year":2021},"citing_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"reference_index":66,"source":"pdf_text","source_observed_at":"2026-05-13T14:22:16.968028Z"},"links":{"cited_paper":"/paper/2112.10752","citing_paper":"/paper/2210.08402"},"observation_digest":"sha256:fef9da203959dc377597e27f239ce262fee74f24beb3d2aec1f18e8a23625b6e","observation_id":"99c14692-d454-403d-bc4b-6462010a28e7","resolution":{"observed_at":"2026-05-13T14:22:17.392195Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-05-24T01:24:00.877132+00:00","source":"crossref_status_cache"},{"observed_at":"2026-05-24T01:24:00.877132+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"High-resolution image synthesis with latent diﬀusion models","venue":null,"work_id":"a1511538-d5e5-4dfe-9992-0a5232df54ab","year":2021},"citing_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"reference_index":67,"source":"pdf_text","source_observed_at":"2026-05-13T14:22:16.968028Z"},"links":{"citing_paper":"/paper/2210.08402"},"observation_digest":"sha256:99a5af9bc954d7ce7fa03f975e91b750d5278c2adae4bf401dff871f0adfa41d","observation_id":"6f1e12cd-4412-4ffc-9f4c-3874561cbb15","resolution":{"observed_at":"2026-05-13T14:22:17.649403Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1007/s11263-015-0816-y","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-30T06:34:18.332950Z","title":"ImageNet Large Scale Visual Recognition Challenge","venue":"International Journal of Computer Vision","work_id":"5fa65a50-c437-40cd-bd09-3ae031477803","year":2015},"citing_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"reference_index":68,"source":"pdf_text","source_observed_at":"2026-05-13T14:22:16.968028Z"},"links":{"citing_paper":"/paper/2210.08402"},"observation_digest":"sha256:d78f74c2188efdcd226e02b0767322a6f430621b2930e72f76601d634d78c839","observation_id":"53e2f703-0d88-4e74-9870-7da28d34d954","resolution":{"observed_at":"2026-05-13T14:22:17.128586Z","resolver_source":"doi","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-07-12T12:50:01.687181+00:00","source":"crossref_status_cache"},{"observed_at":"2026-07-12T12:50:01.687181+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Sara Mahdavi, Rapha Gontijo Lopes, Tim Salimans, Jonathan Ho, David J Fleet, and Mohammad Norouzi","venue":null,"work_id":"e5136e8e-5338-4475-8993-4fb050d5d01d","year":2022},"citing_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"reference_index":69,"source":"pdf_text","source_observed_at":"2026-05-13T14:22:16.968028Z"},"links":{"citing_paper":"/paper/2210.08402"},"observation_digest":"sha256:c91ce2c64bfc907449d4bf826c3b22b8e7eaa310213f16a595129f3cabf3c5f3","observation_id":"cdec15e4-15cf-4b02-bfc0-df905fb195e2","resolution":{"observed_at":"2026-05-13T14:22:17.667437Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Clipfa: Connecting farsi text and images.https://github.com /SajjjadAyobi/CLIPfa","venue":null,"work_id":"5cdd3d03-ea43-4ed6-a3ff-f154ba0759e6","year":2021},"citing_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"reference_index":70,"source":"pdf_text","source_observed_at":"2026-05-13T14:22:16.968028Z"},"links":{"citing_paper":"/paper/2210.08402"},"observation_digest":"sha256:b0733116072da29f0f8bcacb96d6a09b795547f958ca1009cfcea12aa39ed839","observation_id":"95a19437-c64f-4dc5-ae0b-3f21f3f76fa9","resolution":{"observed_at":"2026-05-13T14:22:17.673465Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":null,"venue":null,"work_id":"3c321a36-a325-4758-b0d6-b993c2cb9f5e","year":2022},"citing_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"reference_index":71,"source":"pdf_text","source_observed_at":"2026-05-13T14:22:16.968028Z"},"links":{"citing_paper":"/paper/2210.08402"},"observation_digest":"sha256:4519b7fcf9482ddfbdcf9ef568b8121701781384b5e5dc9e14bab87fc822d7f9","observation_id":"12c6b57d-4c74-4564-9434-a875b925e213","resolution":{"observed_at":"2026-05-13T14:22:17.679346Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2111.02114","last_updated":"2021-11-03T10:16:39Z","snapshot_observed_at":"2026-08-02T08:12:49.547570Z","submitted_at":"2021-11-03T10:16:39Z","title":"LAION-400M: Open Dataset of CLIP-Filtered 400 Million Image-Text Pairs","version":1},"cited_work":{"arxiv_id":"2111.02114","doi":"10.48550/arxiv.2111.02114","metadata_source":"pith","pith_arxiv_id":"2111.02114","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"LAION-400M: Open Dataset of CLIP-Filtered 400 Million Image-Text Pairs","venue":"cs.CV","work_id":"fbf16034-512e-4dd9-a0bd-7ddd23f532a6","year":2021},"citing_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"reference_index":72,"source":"pdf_text","source_observed_at":"2026-05-13T14:22:16.968028Z"},"links":{"cited_paper":"/paper/2111.02114","citing_paper":"/paper/2210.08402"},"observation_digest":"sha256:586fc4e4301f0fd140308c4c50ff41fbf8204d039abbc5828ddd02a2f02b62ad","observation_id":"16dbfd94-8af3-4dbe-b549-d1cb5cafde6f","resolution":{"observed_at":"2026-05-13T14:22:17.398100Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-05-23T16:25:40.426779+00:00","source":"crossref_status_cache"},{"observed_at":"2026-05-23T16:25:40.426779+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Do image classiﬁers generalize across time?, 2019.https://arxiv.org/abs/1906.0 2168","venue":null,"work_id":"ae6f73a7-0460-492a-b76f-1f447c7c6169","year":2019},"citing_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"reference_index":73,"source":"pdf_text","source_observed_at":"2026-05-13T14:22:16.968028Z"},"links":{"citing_paper":"/paper/2210.08402"},"observation_digest":"sha256:fec0be03ab387204eb99eab613d118dcb2c5c430176befbd52ec21e431707028","observation_id":"632a8e8d-1360-43df-976c-5561912a2dae","resolution":{"observed_at":"2026-05-13T14:22:17.716368Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.18653/v1/p18-1238","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Conceptual Captions: A Cleaned, Hypernymed, Image Alt-text Dataset For Automatic Image Captioning","venue":null,"work_id":"9c2e3c36-adea-4b47-9871-777187ce44a0","year":2018},"citing_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"reference_index":74,"source":"pdf_text","source_observed_at":"2026-05-13T14:22:16.968028Z"},"links":{"citing_paper":"/paper/2210.08402"},"observation_digest":"sha256:ab6d105d7274953ed25fbf5e12bf2950bde4251eed63d8d00c999cc0bd1f45c6","observation_id":"2f0752b8-1908-4ec7-a961-64161091f642","resolution":{"observed_at":"2026-05-13T14:22:17.120567Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2107.06383","last_updated":"2021-07-13T20:48:12Z","snapshot_observed_at":"2026-08-18T14:41:48.442811Z","submitted_at":"2021-07-13T20:48:12Z","title":"How Much Can CLIP Benefit Vision-and-Language Tasks?","version":1},"cited_work":{"arxiv_id":"2107.06383","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2107.06383","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"How much can clip beneﬁt vision-and-language tasks?","venue":null,"work_id":"3b4c7819-6f34-4c2d-91df-038dc5d7c576","year":2021},"citing_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"reference_index":75,"source":"pdf_text","source_observed_at":"2026-05-13T14:22:16.968028Z"},"links":{"cited_paper":"/paper/2107.06383","citing_paper":"/paper/2210.08402"},"observation_digest":"sha256:ccd9f1402f7c8af3b1ff38b4adaacf04c78d8ec4fa366c90866896de1722cb1d","observation_id":"13ebeee1-ad8b-49bf-9ba1-1854afecb28b","resolution":{"observed_at":"2026-05-13T14:22:17.404806Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Japanese clip.https://github.com/rinnakk/japanese-clip, May 2022","venue":null,"work_id":"efc0f6ec-590c-4616-9087-adc2ce75314e","year":2022},"citing_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"reference_index":76,"source":"pdf_text","source_observed_at":"2026-05-13T14:22:16.968028Z"},"links":{"citing_paper":"/paper/2210.08402"},"observation_digest":"sha256:9dfed8f3179506305d307ec5b30464bdc0ec2e57681caddfe10d5447beba5ced","observation_id":"d4204377-1308-4e86-bd0f-67011a6bdef9","resolution":{"observed_at":"2026-05-13T14:22:17.733798Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Koclip.https://github.com/jaketae/koc lip, 20201","venue":null,"work_id":"3109b88b-14e2-4925-9ab9-7b169aee801c","year":null},"citing_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"reference_index":77,"source":"pdf_text","source_observed_at":"2026-05-13T14:22:16.968028Z"},"links":{"citing_paper":"/paper/2210.08402"},"observation_digest":"sha256:c3d2383d7d50323c4741bc05c93cfbade930dce4779f0694382b94670de2c438","observation_id":"2a739d6c-be95-4e6d-aa1a-a61268c9806c","resolution":{"observed_at":"2026-05-13T14:22:17.742546Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Wit: Wikipedia-based image text dataset for multimodal multilingual machine learning","venue":null,"work_id":"a891e3be-311e-489e-8385-4aaee3603d4c","year":2021},"citing_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"reference_index":78,"source":"pdf_text","source_observed_at":"2026-05-13T14:22:16.968028Z"},"links":{"citing_paper":"/paper/2210.08402"},"observation_digest":"sha256:a031c81f6e89eb0f42c36681b767e9cb0ea70a08179e69859fccbd737f5714a1","observation_id":"d0c12487-2601-4516-bf19-7f306e75d1e1","resolution":{"observed_at":"2026-05-13T14:22:17.759437Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Image representations learned with unsupervised pre-training contain human-like biases","venue":null,"work_id":"47a96b3a-c090-4804-b411-188ffe9b6ef7","year":2021},"citing_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"reference_index":79,"source":"pdf_text","source_observed_at":"2026-05-13T14:22:16.968028Z"},"links":{"citing_paper":"/paper/2210.08402"},"observation_digest":"sha256:ac59bee7160889208cfe36af2b35f1369d4f63056b39fd372e7215285dd3c3e3","observation_id":"d6baf8c9-1361-43fb-90d4-e65d07fd135d","resolution":{"observed_at":"2026-05-13T14:22:17.763688Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Revisiting unreasonable eﬀectiveness of data in deep learning era","venue":null,"work_id":"be9abb1d-b4ab-460b-94a4-10e9040e383b","year":2017},"citing_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"reference_index":80,"source":"pdf_text","source_observed_at":"2026-05-13T14:22:16.968028Z"},"links":{"citing_paper":"/paper/2210.08402"},"observation_digest":"sha256:f5ea92e05b0faef7b8ca4e9ed0a34ac2354f50db4bdbedd135138d0b7f253217","observation_id":"e96a7139-a404-40e8-9a66-927fac01fcb8","resolution":{"observed_at":"2026-05-13T14:22:17.771892Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Measuring robustness to natural distribution shifts in image classiﬁcation.Advances in Neural Information Processing Systems, 33:18583–18599","venue":null,"work_id":"8dc8747c-209a-419e-b38d-a447eb9acfb3","year":2020},"citing_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"reference_index":81,"source":"pdf_text","source_observed_at":"2026-05-13T14:22:16.968028Z"},"links":{"citing_paper":"/paper/2210.08402"},"observation_digest":"sha256:914c9a15e8884403ea8459a759fb00d289450f76607e0d3f3cbbc97ec3a77b9b","observation_id":"ad1e7fa0-13da-4d67-a442-0834dfef22f7","resolution":{"observed_at":"2026-05-13T14:22:17.781908Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Yfcc100m: The new data in multimedia research.Communications of the ACM, 59(2):64–73","venue":null,"work_id":"1faef290-af65-4ad6-8503-58168fae8a4b","year":2016},"citing_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"reference_index":82,"source":"pdf_text","source_observed_at":"2026-05-13T14:22:16.968028Z"},"links":{"citing_paper":"/paper/2210.08402"},"observation_digest":"sha256:a3f9ec15bad5110425b8c1e776ebf48f155a5b19083244e716d595f7fa5d5dbe","observation_id":"8ec29e37-e9f7-4c83-b7b3-00a88d4bc1c2","resolution":{"observed_at":"2026-05-13T14:22:17.791763Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Multimodal few-shot learning with frozen language models.Advances in Neural Information Processing Systems, 34:200–212","venue":null,"work_id":"2a245ba6-778e-462e-acd6-b876de235bc0","year":2021},"citing_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"reference_index":83,"source":"pdf_text","source_observed_at":"2026-05-13T14:22:16.968028Z"},"links":{"citing_paper":"/paper/2210.08402"},"observation_digest":"sha256:dfc0a3645f81d00bdbd1b169c218e3c489265fb177d710840a9ee12940ffb872","observation_id":"c53690b6-c1cd-4e45-93c4-adf5a0a852c9","resolution":{"observed_at":"2026-05-13T14:22:17.812882Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-10T15:47:23.567466Z","title":"Attention is all you need.Advances in neural information processing systems, 30","venue":null,"work_id":"751efe07-5e91-415c-b3d1-f4734aa26960","year":2017},"citing_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"reference_index":84,"source":"pdf_text","source_observed_at":"2026-05-13T14:22:16.968028Z"},"links":{"citing_paper":"/paper/2210.08402"},"observation_digest":"sha256:1a09c16a9ce454a41ab66d62eaffec3bdb2b1143f4ca701efc80124659b68c7a","observation_id":"9046ba01-1b59-4e23-bda5-5b741aaaddd9","resolution":{"observed_at":"2026-05-13T14:22:17.822119Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1905.13549","last_updated":"2019-11-05T03:56:06Z","snapshot_observed_at":"2026-08-17T14:23:26.258940Z","submitted_at":"2019-05-29T00:27:54Z","title":"Learning Robust Global Representations by Penalizing Local Predictive Power","version":2},"cited_work":{"arxiv_id":"1905.13549","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"1905.13549","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"15 Supplementary Material A Extended Related Work Generative and discriminative theories of vision","venue":null,"work_id":"a19d3579-94db-4d19-8ff6-2eb4fdd08c2d","year":1905},"citing_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"reference_index":85,"source":"pdf_text","source_observed_at":"2026-05-13T14:22:16.968028Z"},"links":{"cited_paper":"/paper/1905.13549","citing_paper":"/paper/2210.08402"},"observation_digest":"sha256:b584443a42446556cdafa96b6278532d8298b877c7411d4943d637bc07763ca4","observation_id":"d0d0e904-5f80-44ca-9ed7-64676e635ef2","resolution":{"observed_at":"2026-05-13T14:22:17.411147Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Large scale image annotation: learning to rank with joint word-image embeddings.Machine learning, 81(1):21–35","venue":null,"work_id":"2e6d7cb5-d2a3-4a93-8b2c-1e9f9d863738","year":2010},"citing_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"reference_index":86,"source":"pdf_text","source_observed_at":"2026-05-13T14:22:16.968028Z"},"links":{"citing_paper":"/paper/2210.08402"},"observation_digest":"sha256:2a63c9cdd0ee2113938dcf88f95f0f2fc3e599a6e8cfa235f44860728305627b","observation_id":"5b438f4e-de19-4a95-a8e2-cd65cb3e9232","resolution":{"observed_at":"2026-05-13T14:22:17.863193Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2109.01903","last_updated":"2022-06-21T21:50:28Z","snapshot_observed_at":"2026-08-19T23:36:17.759822Z","submitted_at":"2021-09-04T17:11:28Z","title":"Robust fine-tuning of zero-shot models","version":3},"cited_work":{"arxiv_id":"2109.01903","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2109.01903","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Li, Simon Kornblith, Rebecca Roelofs, Raphael Gontijo Lopes, Hannaneh Hajishirzi, Ali Farhadi, Hongseok Namkoong, and Ludwig Schmidt","venue":null,"work_id":"2abe2234-d6e4-47fd-bea2-31dcabddba3a","year":2022},"citing_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"reference_index":87,"source":"pdf_text","source_observed_at":"2026-05-13T14:22:16.968028Z"},"links":{"cited_paper":"/paper/2109.01903","citing_paper":"/paper/2210.08402"},"observation_digest":"sha256:34cf9fedfa2e55216506d1e42a0d07f2a5e31f3ff785f56eb5e6422a4f6edf55","observation_id":"b1c5a6a4-7627-48a9-9121-dd4ea04c125f","resolution":{"observed_at":"2026-05-13T14:22:17.430390Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1007/s11263-014-0748-y","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Yang You, Jing Li, Sashank J","venue":"International Journal of Computer Vision","work_id":"2ca4c02d-cc25-4b62-87f3-c6a8b774c264","year":2016},"citing_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"reference_index":88,"source":"pdf_text","source_observed_at":"2026-05-13T14:22:16.968028Z"},"links":{"citing_paper":"/paper/2210.08402"},"observation_digest":"sha256:434c1af3995c6a558847b1f6eac8d22282de797e9e13bf6a633fde387c3c3573","observation_id":"7fac60f6-39ec-4929-b8d9-3ad86dcf0d76","resolution":{"observed_at":"2026-05-13T14:22:17.114676Z","resolver_source":"doi","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Show, attend and tell: Neural image caption generation with visual attention","venue":null,"work_id":"34a2ea6b-146e-4300-b150-68c08491d9a5","year":2048},"citing_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"reference_index":89,"source":"pdf_text","source_observed_at":"2026-05-13T14:22:16.968028Z"},"links":{"citing_paper":"/paper/2210.08402"},"observation_digest":"sha256:32de31a55bd63eb297a07f74b82e4864a14f83e3267f1c605b355ff4378326a7","observation_id":"d13a6af9-1a6b-459a-830c-3a3c45a6ab7a","resolution":{"observed_at":"2026-05-13T14:22:17.541687Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"A study of face obfuscation in imagenet","venue":null,"work_id":"0c8914cc-7a13-4498-952e-f5fb14b51123","year":2022},"citing_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"reference_index":90,"source":"pdf_text","source_observed_at":"2026-05-13T14:22:16.968028Z"},"links":{"citing_paper":"/paper/2210.08402"},"observation_digest":"sha256:583933fc9803c58890c0a6994d43dbdbe56c21f603eb5db9081b6f2239c7d39c","observation_id":"fdf90977-9bf3-40fb-b745-d9a763ec6418","resolution":{"observed_at":"2026-05-13T14:22:17.555343Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":"10.1162/tacl_a_00166","metadata_source":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"doi: 10.1162/tacl_a_00166","venue":"Transactions of the Association for Computational Linguistics","work_id":"c7eea389-d026-476e-b5d6-5a3a13cfe32e","year":2014},"citing_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"reference_index":91,"source":"pdf_text","source_observed_at":"2026-05-13T14:22:16.968028Z"},"links":{"citing_paper":"/paper/2210.08402"},"observation_digest":"sha256:c4efa40e9fafd702c53885088c36f8d23db3b1847e5543bf01bf3fa7c9c9cf17","observation_id":"7712b7bd-b50b-4b34-bab9-ec8aaffa5396","resolution":{"observed_at":"2026-05-13T14:22:17.108946Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-06T21:38:19.290682+00:00","source":"crossref_status_cache"},{"observed_at":"2026-08-06T21:38:19.290682+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2205.01917","last_updated":"2022-06-14T00:48:04Z","snapshot_observed_at":"2026-08-13T15:12:42.567441Z","submitted_at":"2022-05-04T07:01:14Z","title":"CoCa: Contrastive Captioners are Image-Text Foundation Models","version":2},"cited_work":{"arxiv_id":"2205.01917","doi":"10.48550/arxiv.2205.01917","metadata_source":"pith","pith_arxiv_id":"2205.01917","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"CoCa: Contrastive Captioners are Image-Text Foundation Models","venue":"cs.CV","work_id":"5dd5bf10-d548-40ff-9b6c-6735129b27ee","year":2022},"citing_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"reference_index":92,"source":"pdf_text","source_observed_at":"2026-05-13T14:22:16.968028Z"},"links":{"cited_paper":"/paper/2205.01917","citing_paper":"/paper/2210.08402"},"observation_digest":"sha256:723268c7efd44c85588a7d28809f5b28cc6ccce2b791299d80376872f7af1293","observation_id":"aaf81504-946c-4a3e-a200-948c5d85b3d9","resolution":{"observed_at":"2026-05-15T10:53:08.606863Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-05-22T13:22:43.398968+00:00","source":"crossref_status_cache"},{"observed_at":"2026-05-22T13:22:43.398968+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2206.10789","last_updated":"2022-06-22T01:11:29Z","snapshot_observed_at":"2026-08-18T22:18:02.034966Z","submitted_at":"2022-06-22T01:11:29Z","title":"Scaling Autoregressive Models for Content-Rich Text-to-Image Generation","version":1},"cited_work":{"arxiv_id":"2206.10789","doi":"10.48550/arxiv.2206.10789","metadata_source":"pith","pith_arxiv_id":"2206.10789","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Scaling Autoregressive Models for Content-Rich Text-to-Image Generation","venue":"cs.CV","work_id":"0a105815-ff2e-43ce-8566-966cdcae1af4","year":2022},"citing_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"reference_index":93,"source":"pdf_text","source_observed_at":"2026-05-13T14:22:16.968028Z"},"links":{"cited_paper":"/paper/2206.10789","citing_paper":"/paper/2210.08402"},"observation_digest":"sha256:5666e49da4ebc81fa99ff17a4d50a4d5258f4c4a9a5c9db3b74fab0f6ddd249e","observation_id":"55fb41e9-13c6-47fe-ab76-b0d73638b582","resolution":{"observed_at":"2026-05-13T14:22:17.446645Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1910.04867","last_updated":"2020-02-21T13:36:15Z","snapshot_observed_at":"2026-08-09T06:48:42.729935Z","submitted_at":"2019-10-01T17:06:29Z","title":"A Large-scale Study of Representation Learning with the Visual Task Adaptation Benchmark","version":2},"cited_work":{"arxiv_id":"1910.04867","doi":"10.48550/arxiv.1910.04867","metadata_source":"pith","pith_arxiv_id":"1910.04867","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"A Large-scale Study of Representation Learning with the Visual Task Adaptation Benchmark","venue":"cs.CV","work_id":"eb743d69-6704-47c1-bb0f-76520dd00c3d","year":2019},"citing_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"reference_index":94,"source":"pdf_text","source_observed_at":"2026-05-13T14:22:16.968028Z"},"links":{"cited_paper":"/paper/1910.04867","citing_paper":"/paper/2210.08402"},"observation_digest":"sha256:bce5489bac9900ea62921b8ce1f1b71a47861db9ca406ad7e466987051c6bf7b","observation_id":"29eb3779-a7ea-4b5e-9c0c-a7991d6c29a7","resolution":{"observed_at":"2026-05-17T22:12:05.852900Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Scaling vision transformers","venue":null,"work_id":"942cf134-4d42-43e6-9db2-84d09cb0ec35","year":null},"citing_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"reference_index":95,"source":"pdf_text","source_observed_at":"2026-05-13T14:22:16.968028Z"},"links":{"citing_paper":"/paper/2210.08402"},"observation_digest":"sha256:ccc78dfdd10fa24c9e39241f029f6e40ca5ae553ae48debc9242023cdf90a653","observation_id":"64d88ef4-a864-498e-9cc8-be3c607d9a55","resolution":{"observed_at":"2026-05-13T14:22:17.643387Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2106.04560","last_updated":"2022-06-20T09:13:51Z","snapshot_observed_at":"2026-08-22T02:54:03.990193Z","submitted_at":"2021-06-08T17:47:39Z","title":"Scaling Vision Transformers","version":2},"cited_work":{"arxiv_id":"2106.04560","doi":"10.48550/arxiv.2106.04560","metadata_source":"arxiv_reference","pith_arxiv_id":"2106.04560","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Scaling vision transform- ers, 6 2021","venue":"arXiv (Cornell University)","work_id":"bed1e12d-8db3-4995-a609-386387c6cb86","year":2022},"citing_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"reference_index":96,"source":"pdf_text","source_observed_at":"2026-05-13T14:22:16.968028Z"},"links":{"cited_paper":"/paper/2106.04560","citing_paper":"/paper/2210.08402"},"observation_digest":"sha256:afde73c98de243f461ebc8d0086bf1d6870851f7e7744943d0a07d3fe6a9fda1","observation_id":"b83230e8-7f76-4009-a14e-51caef88ada1","resolution":{"observed_at":"2026-05-13T14:22:17.095075Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2106.04560","last_updated":"2022-06-20T09:13:51Z","snapshot_observed_at":"2026-08-22T02:54:03.990193Z","submitted_at":"2021-06-08T17:47:39Z","title":"Scaling Vision Transformers","version":2},"cited_work":{"arxiv_id":"2106.04560","doi":"10.48550/arxiv.2106.04560","metadata_source":"arxiv_reference","pith_arxiv_id":"2106.04560","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Scaling vision transform- ers, 6 2021","venue":"arXiv (Cornell University)","work_id":"bed1e12d-8db3-4995-a609-386387c6cb86","year":2022},"citing_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"reference_index":97,"source":"pdf_text","source_observed_at":"2026-05-13T14:22:16.968028Z"},"links":{"cited_paper":"/paper/2106.04560","citing_paper":"/paper/2210.08402"},"observation_digest":"sha256:04f75b32238f5d9987cbf2c7a94e9d602cf7e34a89fce7ca7de0cdeee57d078f","observation_id":"614cd53c-7570-4844-80a3-6a848526af84","resolution":{"observed_at":"2026-05-13T14:22:17.464938Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2111.07991","last_updated":"2022-06-22T14:43:02Z","snapshot_observed_at":"2026-08-17T08:32:51.676768Z","submitted_at":"2021-11-15T18:53:48Z","title":"LiT: Zero-Shot Transfer with Locked-image text Tuning","version":3},"cited_work":{"arxiv_id":"2111.07991","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2111.07991","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Lit: Zero-shot transfer with locked-image text tuning","venue":null,"work_id":"12fcc618-8b5e-4778-be4c-419d7e0bc22b","year":2021},"citing_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"reference_index":98,"source":"pdf_text","source_observed_at":"2026-05-13T14:22:16.968028Z"},"links":{"cited_paper":"/paper/2111.07991","citing_paper":"/paper/2210.08402"},"observation_digest":"sha256:0c987e33c5d6633498297095c7fbe097df4dfa41b9edbf57079b38a46097e2a6","observation_id":"cd6e2c60-4785-40f7-b350-b5c8c9ec75c6","resolution":{"observed_at":"2026-05-13T14:22:17.472579Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Stackgan: Text to photo-realistic image synthesis with stacked generative adversarial networks","venue":null,"work_id":"85682781-1f1f-4ede-9a48-104a981ea2ba","year":2017},"citing_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"reference_index":99,"source":"pdf_text","source_observed_at":"2026-05-13T14:22:16.968028Z"},"links":{"citing_paper":"/paper/2210.08402"},"observation_digest":"sha256:e8a6828b6c76544c573c78868707faa63ac5d50c36aa046ec866ac384fafd5e8","observation_id":"e504566f-e411-4c67-a40d-35aa47c3f0f3","resolution":{"observed_at":"2026-05-13T14:22:17.493976Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2112.03109","last_updated":"2022-04-01T06:22:42Z","snapshot_observed_at":"2026-08-18T22:43:08.877381Z","submitted_at":"2021-12-06T15:22:05Z","title":"General Facial Representation Learning in a Visual-Linguistic Manner","version":3},"cited_work":{"arxiv_id":"2112.03109","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2112.03109","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"General facial representa- tion learning in a visual-linguistic manner","venue":null,"work_id":"950874ea-83ff-4853-b9ca-d8226855b54d","year":2021},"citing_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"reference_index":100,"source":"pdf_text","source_observed_at":"2026-05-13T14:22:16.968028Z"},"links":{"cited_paper":"/paper/2112.03109","citing_paper":"/paper/2210.08402"},"observation_digest":"sha256:336b4b65f5064e2c98c4586756387445a4716bc301ce640b5e7831db08f4600d","observation_id":"2c61a09f-6c3c-4880-8614-a2f1378701f8","resolution":{"observed_at":"2026-05-13T14:22:17.481554Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":null,"venue":null,"work_id":"f3e3bcc6-6949-4db0-b1e0-a4e9636a83be","year":null},"citing_paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models","version":1},"reference_index":101,"source":"pdf_text","source_observed_at":"2026-05-13T14:22:16.968028Z"},"links":{"citing_paper":"/paper/2210.08402"},"observation_digest":"sha256:33e11e6294a599311791c2e914926ff88481b1efa7498646c95d886b71dbdea3","observation_id":"9de8cc05-7d2d-4a8a-bae1-d7c4980c0f56","resolution":{"observed_at":"2026-05-13T14:22:17.598771Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2210.08402","last_updated":"2022-10-16T00:08:18Z","latest_version":1,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-13T17:36:16.794649Z","submitted_at":"2022-10-16T00:08:18Z","title":"LAION-5B: An open large-scale dataset for training next generation image-text models"},"reference_resolution":{"displayed":100,"state_counts":{"malformed_identifier":1,"metadata_mismatch":9,"parse_uncertain":0,"unresolved":3,"verified_exact":34,"verified_fuzzy":53},"total_outbound_references":104},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-22T06:32:14.747728+00:00","source":"crossref"},{"observed_at":"2026-08-22T06:32:06.552537+00:00","source":"retraction_watch"}],"thesis":"As of 22 August 2026, this Paper Citation Record lists 100 of 104 outbound references and 95 inbound Pith citation observations for arXiv:2210.08402."}