{"as_of":"2026-08-09T23:07:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:b11530e1900c9a1113f40c39f94dd19aa0b5ff10183ffb3cf4c66df3d7c930aa","coverage":[{"denominator":32,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":32,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-05T17:34:02.646497Z","state":"measured"},{"denominator":32,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":32,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-09T06:31:02.800959+00:00","state":"measured"},{"denominator":0,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[],"links":{"evidence":"/evidence","html":"/paper/2508.16089/citation-record","integrity":"/paper/2508.16089/integrity","json":"/paper/2508.16089/citation-record.json","paper":"/paper/2508.16089"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T17:34:07.212934Z","title":"Vlmo: Unified vision-language pre-training with mixture-of-modality- experts","venue":null,"work_id":"e6293d97-a99d-497c-b97c-a59884d6c491","year":2022},"citing_paper":{"arxiv_id":"2508.16089","last_updated":"2025-08-22T04:59:08Z","snapshot_observed_at":"2026-08-09T06:44:04.445337Z","submitted_at":"2025-08-22T04:59:08Z","title":"Two-flow Feedback Multi-scale Progressive Generative Adversarial Network","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-05T17:33:59.368520Z"},"links":{"citing_paper":"/paper/2508.16089"},"observation_digest":"sha256:87d4bd2d920be27593d72e1e16085a5e16f8937d3b8b6e2eac076b3760356e7c","observation_id":"807391ab-ce77-44c8-b90c-212a12fb905f","resolution":{"observed_at":"2026-08-05T17:34:07.275659Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-05T17:34:07.044125Z","title":"Automatic image processing algorithm for light en- vironment optimization based on multimodal neural network model","venue":null,"work_id":"71e9639a-f689-49cc-90ea-5224eb254ceb","year":2022},"citing_paper":{"arxiv_id":"2508.16089","last_updated":"2025-08-22T04:59:08Z","snapshot_observed_at":"2026-08-09T06:44:04.445337Z","submitted_at":"2025-08-22T04:59:08Z","title":"Two-flow Feedback Multi-scale Progressive Generative Adversarial Network","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-05T17:33:59.484911Z"},"links":{"citing_paper":"/paper/2508.16089"},"observation_digest":"sha256:4cef0e4b299deb38355ad550978c2558c7c614980dec470c1fc5dbe833b1ef83","observation_id":"64590cfe-e14f-49ad-827e-36655f4e277a","resolution":{"observed_at":"2026-08-05T17:34:07.144592Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2111.13587","last_updated":"2022-03-27T04:24:27Z","snapshot_observed_at":"2026-08-06T05:36:16.829512Z","submitted_at":"2021-11-24T05:44:31Z","title":"Adaptive Fourier Neural Operators: Efficient Token Mixers for Transformers","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2111.13587","snapshot_observed_at":"2026-08-05T17:33:59.612044Z","title":"Adaptive fourier neural operators: Efficient token mixers for transformers","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2508.16089","last_updated":"2025-08-22T04:59:08Z","snapshot_observed_at":"2026-08-09T06:44:04.445337Z","submitted_at":"2025-08-22T04:59:08Z","title":"Two-flow Feedback Multi-scale Progressive Generative Adversarial Network","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-05T17:33:59.612044Z"},"links":{"cited_paper":"/paper/2111.13587","citing_paper":"/paper/2508.16089"},"observation_digest":"sha256:2189fd4ce6223684a1e92ac7800b894ac34f6809f277b6a5082dbd8231d798e7","observation_id":"effea056-ae49-451e-beaa-c449ba074cc6","resolution":{"observed_at":"2026-08-05T17:33:59.612044Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T17:34:06.892507Z","title":"Crd-cgan: Category- consistent and relativistic constraints for diverse text-to-image genera- tion","venue":null,"work_id":"96e80c20-9343-471b-992b-0a94ff017042","year":2024},"citing_paper":{"arxiv_id":"2508.16089","last_updated":"2025-08-22T04:59:08Z","snapshot_observed_at":"2026-08-09T06:44:04.445337Z","submitted_at":"2025-08-22T04:59:08Z","title":"Two-flow Feedback Multi-scale Progressive Generative Adversarial Network","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-05T17:33:59.677365Z"},"links":{"citing_paper":"/paper/2508.16089"},"observation_digest":"sha256:9c2e93b84f3278bfcb17c0bbf5a7080b9f6a9e04ce4d09d72dba9b3798516d5f","observation_id":"e1f2da3c-ca74-4e8e-9c18-5197e27e4e0e","resolution":{"observed_at":"2026-08-05T17:34:06.948332Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-05T17:34:06.744140Z","title":"Language is not all you need: Aligning perception with language models","venue":null,"work_id":"24d77274-b42f-4df3-a532-944dc40cc2df","year":2023},"citing_paper":{"arxiv_id":"2508.16089","last_updated":"2025-08-22T04:59:08Z","snapshot_observed_at":"2026-08-09T06:44:04.445337Z","submitted_at":"2025-08-22T04:59:08Z","title":"Two-flow Feedback Multi-scale Progressive Generative Adversarial Network","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-05T17:33:59.837808Z"},"links":{"citing_paper":"/paper/2508.16089"},"observation_digest":"sha256:346b6518168fcfbb6f57a5878baa439e9fdfc48ac0a4f50cf9466d40efe30442","observation_id":"87c69aa9-49dd-4e08-b790-ed7954e39c91","resolution":{"observed_at":"2026-08-05T17:34:06.803936Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-05T17:34:06.609454Z","title":"Adaptive frequency filters as efficient global token mixers","venue":null,"work_id":"a825e5a0-d406-4055-a0e4-1ee5473c4e9c","year":2023},"citing_paper":{"arxiv_id":"2508.16089","last_updated":"2025-08-22T04:59:08Z","snapshot_observed_at":"2026-08-09T06:44:04.445337Z","submitted_at":"2025-08-22T04:59:08Z","title":"Two-flow Feedback Multi-scale Progressive Generative Adversarial Network","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-05T17:33:59.909457Z"},"links":{"citing_paper":"/paper/2508.16089"},"observation_digest":"sha256:4a4b07d827dd844a0dea64b22651a779a30f944b3e431e9f3b480cf097920e00","observation_id":"be22b351-0e5e-44a2-8a4a-9b8400ff3ff9","resolution":{"observed_at":"2026-08-05T17:34:06.692902Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-05T17:34:06.419886Z","title":"Fast and efficient image generation using variational autoencoders and k-nearest neighbor oversampling approach","venue":null,"work_id":"5b38264f-96be-4538-a525-d464abd9c90e","year":2023},"citing_paper":{"arxiv_id":"2508.16089","last_updated":"2025-08-22T04:59:08Z","snapshot_observed_at":"2026-08-09T06:44:04.445337Z","submitted_at":"2025-08-22T04:59:08Z","title":"Two-flow Feedback Multi-scale Progressive Generative Adversarial Network","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-05T17:33:59.987521Z"},"links":{"citing_paper":"/paper/2508.16089"},"observation_digest":"sha256:3de59412be478255eaf4ed73f4762eac4b7c6e91026e6f8dbbf3458cbbf1525a","observation_id":"299ed658-aa87-426b-a99b-c2c3cc54a161","resolution":{"observed_at":"2026-08-05T17:34:06.511813Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-05T17:34:06.278219Z","title":"An underwater image enhancement method for a preprocessing framework based on generative adversarial network","venue":null,"work_id":"01c21a62-831b-4ae4-b293-1c3208c28bb7","year":2023},"citing_paper":{"arxiv_id":"2508.16089","last_updated":"2025-08-22T04:59:08Z","snapshot_observed_at":"2026-08-09T06:44:04.445337Z","submitted_at":"2025-08-22T04:59:08Z","title":"Two-flow Feedback Multi-scale Progressive Generative Adversarial Network","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-05T17:34:00.057732Z"},"links":{"citing_paper":"/paper/2508.16089"},"observation_digest":"sha256:12e95a9f3d91e47a3356078de2b9bf82ea310ab61182edf42b40187f9f623b6f","observation_id":"946f70a0-0285-4c93-b365-e48688ced583","resolution":{"observed_at":"2026-08-05T17:34:06.343822Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T17:34:00.128896Z","title":"Vilt: Vision-and-language transformer without convolution or region supervision","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2508.16089","last_updated":"2025-08-22T04:59:08Z","snapshot_observed_at":"2026-08-09T06:44:04.445337Z","submitted_at":"2025-08-22T04:59:08Z","title":"Two-flow Feedback Multi-scale Progressive Generative Adversarial Network","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-05T17:34:00.128896Z"},"links":{"citing_paper":"/paper/2508.16089"},"observation_digest":"sha256:9d4dcfc4c4b6a429180db3833470beee8328f9effb297ce69f65028db9171ba8","observation_id":"d715a7a3-7d13-4a23-99d7-375b91b6b5c5","resolution":{"observed_at":"2026-08-05T17:34:00.128896Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T17:34:00.199286Z","title":"Blip-2: Bootstrapping language-image pre-training with frozen image encoders and large language models","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2508.16089","last_updated":"2025-08-22T04:59:08Z","snapshot_observed_at":"2026-08-09T06:44:04.445337Z","submitted_at":"2025-08-22T04:59:08Z","title":"Two-flow Feedback Multi-scale Progressive Generative Adversarial Network","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-05T17:34:00.199286Z"},"links":{"citing_paper":"/paper/2508.16089"},"observation_digest":"sha256:97f822134cd119ed49fc89fcb43ab1879af62536894b089e22950ef76324166f","observation_id":"d33d5f5e-7cde-4e19-aa61-8daee01a1ad5","resolution":{"observed_at":"2026-08-05T17:34:00.199286Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T17:34:00.309809Z","title":"Blip: Bootstrapping language-image pre-training for unified vision-language understanding and generation","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2508.16089","last_updated":"2025-08-22T04:59:08Z","snapshot_observed_at":"2026-08-09T06:44:04.445337Z","submitted_at":"2025-08-22T04:59:08Z","title":"Two-flow Feedback Multi-scale Progressive Generative Adversarial Network","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-05T17:34:00.309809Z"},"links":{"citing_paper":"/paper/2508.16089"},"observation_digest":"sha256:2db873294a52ed321552befd8615601f854c8db98331837eb4410d8e8fc2d057","observation_id":"79da46f4-044a-4ecb-b850-f74b304d4705","resolution":{"observed_at":"2026-08-05T17:34:00.309809Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T17:34:06.030516Z","title":"Align before fuse: Vision and language representation learning with momentum distillation","venue":null,"work_id":"6d32332c-b888-4911-82bd-301675a7ec97","year":2021},"citing_paper":{"arxiv_id":"2508.16089","last_updated":"2025-08-22T04:59:08Z","snapshot_observed_at":"2026-08-09T06:44:04.445337Z","submitted_at":"2025-08-22T04:59:08Z","title":"Two-flow Feedback Multi-scale Progressive Generative Adversarial Network","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-05T17:34:00.454667Z"},"links":{"citing_paper":"/paper/2508.16089"},"observation_digest":"sha256:991ae2a568b88888714bfc159d0d6d26ca0daf9d2f37121963bb046ec5db0728","observation_id":"10a08b3d-d280-4753-a246-c984f741afb7","resolution":{"observed_at":"2026-08-05T17:34:06.154262Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2311.01378","last_updated":"2024-02-05T03:46:00Z","snapshot_observed_at":"2026-07-31T21:45:51.138808Z","submitted_at":"2023-11-02T16:34:33Z","title":"Vision-Language Foundation Models as Effective Robot Imitators","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2311.01378","snapshot_observed_at":"2026-08-05T17:34:00.544575Z","title":"Vision- language foundation models as effective robot imitators","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2508.16089","last_updated":"2025-08-22T04:59:08Z","snapshot_observed_at":"2026-08-09T06:44:04.445337Z","submitted_at":"2025-08-22T04:59:08Z","title":"Two-flow Feedback Multi-scale Progressive Generative Adversarial Network","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-05T17:34:00.544575Z"},"links":{"cited_paper":"/paper/2311.01378","citing_paper":"/paper/2508.16089"},"observation_digest":"sha256:e1ef473ea772d783444b73f5930f2ded0e9c5260d271e360f089de3ea5c4a4df","observation_id":"35f40323-ed57-40d4-b829-b4e32bb89201","resolution":{"observed_at":"2026-08-05T17:34:00.544575Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T17:34:05.807250Z","title":"Scaling language-image pre-training via masking","venue":null,"work_id":"f7db37dd-7eaf-4c70-ad8f-5db723dc0f29","year":2023},"citing_paper":{"arxiv_id":"2508.16089","last_updated":"2025-08-22T04:59:08Z","snapshot_observed_at":"2026-08-09T06:44:04.445337Z","submitted_at":"2025-08-22T04:59:08Z","title":"Two-flow Feedback Multi-scale Progressive Generative Adversarial Network","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-05T17:34:00.619985Z"},"links":{"citing_paper":"/paper/2508.16089"},"observation_digest":"sha256:1632e5e65f6a3ef89602c6e9277aae7ee0b505f4ed55f7d87257138123a8ec9a","observation_id":"921cecd7-bb63-4701-bc08-856a750a01be","resolution":{"observed_at":"2026-08-05T17:34:05.930398Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-05T17:34:05.653261Z","title":"Novel creation method of feature graphics for image generation based on deep learning algorithms","venue":null,"work_id":"7cea8c46-4cde-4eb2-96e6-e64bdc04bfff","year":2023},"citing_paper":{"arxiv_id":"2508.16089","last_updated":"2025-08-22T04:59:08Z","snapshot_observed_at":"2026-08-09T06:44:04.445337Z","submitted_at":"2025-08-22T04:59:08Z","title":"Two-flow Feedback Multi-scale Progressive Generative Adversarial Network","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-05T17:34:00.691859Z"},"links":{"citing_paper":"/paper/2508.16089"},"observation_digest":"sha256:a54c5f265da87f375bc609188102a7f870cea2db4ebb33cf63abb3a81b22c946","observation_id":"7feb6fbd-6f91-4ce3-b933-acff55a14ded","resolution":{"observed_at":"2026-08-05T17:34:05.706933Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-05T17:34:05.450288Z","title":"Comparing recognition performance and robustness of multimodal deep learning models for multimodal emotion recognition","venue":null,"work_id":"f7922469-93b4-4077-94c2-fc618d331cfd","year":2021},"citing_paper":{"arxiv_id":"2508.16089","last_updated":"2025-08-22T04:59:08Z","snapshot_observed_at":"2026-08-09T06:44:04.445337Z","submitted_at":"2025-08-22T04:59:08Z","title":"Two-flow Feedback Multi-scale Progressive Generative Adversarial Network","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-05T17:34:00.746627Z"},"links":{"citing_paper":"/paper/2508.16089"},"observation_digest":"sha256:a4b8bf72d62040cb83dd5fde2576cec7bd699bf006a19ade643f51eb87d089a6","observation_id":"0fe6d947-a3a7-4014-904f-75a62fcc9ace","resolution":{"observed_at":"2026-08-05T17:34:05.531871Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-05T17:34:05.326031Z","title":"Cogan: Cooperatively trained conditional and unconditional gan for person image generation","venue":null,"work_id":"365f6786-dc4e-4d27-b1de-4a458a33d636","year":2023},"citing_paper":{"arxiv_id":"2508.16089","last_updated":"2025-08-22T04:59:08Z","snapshot_observed_at":"2026-08-09T06:44:04.445337Z","submitted_at":"2025-08-22T04:59:08Z","title":"Two-flow Feedback Multi-scale Progressive Generative Adversarial Network","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-05T17:34:00.861661Z"},"links":{"citing_paper":"/paper/2508.16089"},"observation_digest":"sha256:d2d1557d7587cf40a0ab46d1c6a5bea65fcef71ff803f5a017a958a156c9b53d","observation_id":"5ed001aa-81d2-4c8c-a99e-f81dbc9d923f","resolution":{"observed_at":"2026-08-05T17:34:05.382658Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T17:34:00.987954Z","title":"Learning transferable visual models from natural language supervision","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2508.16089","last_updated":"2025-08-22T04:59:08Z","snapshot_observed_at":"2026-08-09T06:44:04.445337Z","submitted_at":"2025-08-22T04:59:08Z","title":"Two-flow Feedback Multi-scale Progressive Generative Adversarial Network","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-05T17:34:00.987954Z"},"links":{"citing_paper":"/paper/2508.16089"},"observation_digest":"sha256:a486376f0b42b2742ca091eb24191d890c6cfad82b35a83ced87838acbd4b202","observation_id":"29a9f4b4-55b6-4509-92fa-82439cfa4e7a","resolution":{"observed_at":"2026-08-05T17:34:00.987954Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T17:34:05.126308Z","title":"Explor- ing the limits of transfer learning with a unified text-to-text transformer","venue":null,"work_id":"2e0339ff-a5ec-46dc-a51d-9c481cb15bb0","year":2020},"citing_paper":{"arxiv_id":"2508.16089","last_updated":"2025-08-22T04:59:08Z","snapshot_observed_at":"2026-08-09T06:44:04.445337Z","submitted_at":"2025-08-22T04:59:08Z","title":"Two-flow Feedback Multi-scale Progressive Generative Adversarial Network","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-05T17:34:01.109704Z"},"links":{"citing_paper":"/paper/2508.16089"},"observation_digest":"sha256:24cc53f14bdc15f59ccb5241cef85c18c15cf08e18923ad8ab0d245d74017082","observation_id":"d0867e17-8cbf-4520-949f-4a43441df9bc","resolution":{"observed_at":"2026-08-05T17:34:05.208888Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T17:34:01.214203Z","title":"Generative multimodal models are in-context learners","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2508.16089","last_updated":"2025-08-22T04:59:08Z","snapshot_observed_at":"2026-08-09T06:44:04.445337Z","submitted_at":"2025-08-22T04:59:08Z","title":"Two-flow Feedback Multi-scale Progressive Generative Adversarial Network","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-05T17:34:01.214203Z"},"links":{"citing_paper":"/paper/2508.16089"},"observation_digest":"sha256:7512021401ecb406bf29571e9fbcbcea79ff73af8ecb38d32dd6a219928fc279","observation_id":"8ad94daa-7b47-4bee-a05c-ffe133b0f482","resolution":{"observed_at":"2026-08-05T17:34:01.214203Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T17:34:05.040752Z","title":"Attentional generative adversarial networks with representativeness and diversity for generating text to realistic image","venue":null,"work_id":"cb482128-7b4e-41a5-922c-a20f2875c8b1","year":2020},"citing_paper":{"arxiv_id":"2508.16089","last_updated":"2025-08-22T04:59:08Z","snapshot_observed_at":"2026-08-09T06:44:04.445337Z","submitted_at":"2025-08-22T04:59:08Z","title":"Two-flow Feedback Multi-scale Progressive Generative Adversarial Network","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-05T17:34:01.370279Z"},"links":{"citing_paper":"/paper/2508.16089"},"observation_digest":"sha256:b5584f3c752cf43cb1421d905f48825e316d57ccb16e13aeae6d96a4add36295","observation_id":"c329a4c6-9edb-4265-91cd-8ef687e88ab1","resolution":{"observed_at":"2026-08-05T17:34:05.093550Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-05T17:34:04.841924Z","title":"Improving the quality of image generation in art with top-k training and cyclic generative methods","venue":null,"work_id":"b93c7bd4-18c4-47cd-a0a6-89e9b34d3b10","year":2023},"citing_paper":{"arxiv_id":"2508.16089","last_updated":"2025-08-22T04:59:08Z","snapshot_observed_at":"2026-08-09T06:44:04.445337Z","submitted_at":"2025-08-22T04:59:08Z","title":"Two-flow Feedback Multi-scale Progressive Generative Adversarial Network","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-05T17:34:01.440570Z"},"links":{"citing_paper":"/paper/2508.16089"},"observation_digest":"sha256:af7fe9e02f4d226555bbf0ad9381e18fb399ab8cb836f08b084981d0700c6c80","observation_id":"b683f7ec-3cf0-45da-b83d-23cfa7dfcc4f","resolution":{"observed_at":"2026-08-05T17:34:04.957270Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-05T17:34:04.596188Z","title":"Image generation and recognition technology based on attention residual gan","venue":null,"work_id":"1a066ce0-08ba-408e-b54d-c7cf0b382ac3","year":2023},"citing_paper":{"arxiv_id":"2508.16089","last_updated":"2025-08-22T04:59:08Z","snapshot_observed_at":"2026-08-09T06:44:04.445337Z","submitted_at":"2025-08-22T04:59:08Z","title":"Two-flow Feedback Multi-scale Progressive Generative Adversarial Network","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-05T17:34:01.562047Z"},"links":{"citing_paper":"/paper/2508.16089"},"observation_digest":"sha256:87830d5e84a40d52d287b4efcc7797c7ea825d32a566713aec8a89bf0546bb98","observation_id":"f3705f24-c791-4f63-a289-3f61ecc1505f","resolution":{"observed_at":"2026-08-05T17:34:04.700687Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2208.10442","last_updated":"2022-08-31T02:26:45Z","snapshot_observed_at":"2026-08-09T06:43:33.951821Z","submitted_at":"2022-08-22T16:55:04Z","title":"Image as a Foreign Language: BEiT Pretraining for All Vision and Vision-Language Tasks","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2208.10442","snapshot_observed_at":"2026-08-05T17:34:01.707250Z","title":"Image as a foreign language: Beit pretraining for all vision and vision-language tasks","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2508.16089","last_updated":"2025-08-22T04:59:08Z","snapshot_observed_at":"2026-08-09T06:44:04.445337Z","submitted_at":"2025-08-22T04:59:08Z","title":"Two-flow Feedback Multi-scale Progressive Generative Adversarial Network","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-05T17:34:01.707250Z"},"links":{"cited_paper":"/paper/2208.10442","citing_paper":"/paper/2508.16089"},"observation_digest":"sha256:aa0706f194f53ae2d37fc527b76c0cdc05272ea375c8079ee3035a9a7d6d80d1","observation_id":"4b80da1b-58b7-46f3-89d4-0af64770e6a8","resolution":{"observed_at":"2026-08-05T17:34:01.707250Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T17:34:04.292654Z","title":"Rca-gan: An improved image denoising algorithm based on generative adversarial networks","venue":null,"work_id":"610f4a6b-5018-40d4-8eb3-df1d27a24a7c","year":2023},"citing_paper":{"arxiv_id":"2508.16089","last_updated":"2025-08-22T04:59:08Z","snapshot_observed_at":"2026-08-09T06:44:04.445337Z","submitted_at":"2025-08-22T04:59:08Z","title":"Two-flow Feedback Multi-scale Progressive Generative Adversarial Network","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-05T17:34:01.779068Z"},"links":{"citing_paper":"/paper/2508.16089"},"observation_digest":"sha256:7abc7ff220e9766cec1d6ff03bfc000777b3c814135d6b215581ba78a44736ef","observation_id":"52f2e878-0718-4778-b710-d7566931bf27","resolution":{"observed_at":"2026-08-05T17:34:04.479728Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2407.05600","last_updated":"2024-10-28T14:08:13Z","snapshot_observed_at":"2026-08-09T20:22:09.850211Z","submitted_at":"2024-07-08T04:30:53Z","title":"GenArtist: Multimodal LLM as an Agent for Unified Image Generation and Editing","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2407.05600","snapshot_observed_at":"2026-08-05T17:34:01.898001Z","title":"Genartist: Multimodal llm as an agent for unified image generation and editing","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2508.16089","last_updated":"2025-08-22T04:59:08Z","snapshot_observed_at":"2026-08-09T06:44:04.445337Z","submitted_at":"2025-08-22T04:59:08Z","title":"Two-flow Feedback Multi-scale Progressive Generative Adversarial Network","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-05T17:34:01.898001Z"},"links":{"cited_paper":"/paper/2407.05600","citing_paper":"/paper/2508.16089"},"observation_digest":"sha256:99778f57e24c72422ec2b4a67309a3d9f7183481936bb67d52971098a363b3cf","observation_id":"8b5c4c48-daf3-46d8-beda-09af2f5425c9","resolution":{"observed_at":"2026-08-05T17:34:01.898001Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T17:34:04.018196Z","title":"Lpgan: A lbp-based proportional input generative adversarial network for image fusion","venue":null,"work_id":"ebbea19b-950e-4301-9102-324d0b96aa03","year":2023},"citing_paper":{"arxiv_id":"2508.16089","last_updated":"2025-08-22T04:59:08Z","snapshot_observed_at":"2026-08-09T06:44:04.445337Z","submitted_at":"2025-08-22T04:59:08Z","title":"Two-flow Feedback Multi-scale Progressive Generative Adversarial Network","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-05T17:34:02.040551Z"},"links":{"citing_paper":"/paper/2508.16089"},"observation_digest":"sha256:aacf946bcf54e05c34834ea3d819bf1d5f8626b007fd8392697335aeab30daa3","observation_id":"62e09caa-9ced-409a-b069-f9baa68df613","resolution":{"observed_at":"2026-08-05T17:34:04.143415Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-05T17:34:03.807816Z","title":"Vsa: Learning varied-size window attention in vision transformers","venue":null,"work_id":"5dfdfe8f-cf7c-4d6a-b65d-b49f64dfcd85","year":2022},"citing_paper":{"arxiv_id":"2508.16089","last_updated":"2025-08-22T04:59:08Z","snapshot_observed_at":"2026-08-09T06:44:04.445337Z","submitted_at":"2025-08-22T04:59:08Z","title":"Two-flow Feedback Multi-scale Progressive Generative Adversarial Network","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-05T17:34:02.124721Z"},"links":{"citing_paper":"/paper/2508.16089"},"observation_digest":"sha256:b19c3e42b894c8b7a8fe7cf857154da2510e3dd8264e23440a64c2f1e3d58099","observation_id":"b900d4cd-3e2c-43a4-8d71-6a1b80ff14b4","resolution":{"observed_at":"2026-08-05T17:34:03.894380Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-05T17:34:03.533013Z","title":"Joint generative image deblurring aided by edge attention prior and dynamic kernel selection","venue":null,"work_id":"b08086bc-2497-4191-8543-393a949cd2c6","year":2021},"citing_paper":{"arxiv_id":"2508.16089","last_updated":"2025-08-22T04:59:08Z","snapshot_observed_at":"2026-08-09T06:44:04.445337Z","submitted_at":"2025-08-22T04:59:08Z","title":"Two-flow Feedback Multi-scale Progressive Generative Adversarial Network","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-05T17:34:02.235743Z"},"links":{"citing_paper":"/paper/2508.16089"},"observation_digest":"sha256:7e328ea6aacb83af0a282962a0d02e1bba980ade3ce994aa9f2e246188aaf57b","observation_id":"b56fd965-992a-4f7f-ac04-fc18e07569a3","resolution":{"observed_at":"2026-08-05T17:34:03.657397Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-05T17:34:03.319710Z","title":"Cyclic generative attention- adversarial network for low-light image enhancement","venue":null,"work_id":"5b2d68bd-9ae9-49d9-b596-e79f3e4de93e","year":2023},"citing_paper":{"arxiv_id":"2508.16089","last_updated":"2025-08-22T04:59:08Z","snapshot_observed_at":"2026-08-09T06:44:04.445337Z","submitted_at":"2025-08-22T04:59:08Z","title":"Two-flow Feedback Multi-scale Progressive Generative Adversarial Network","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-05T17:34:02.415941Z"},"links":{"citing_paper":"/paper/2508.16089"},"observation_digest":"sha256:eba56c3821f9c30fd1c1da5257dbcb9635dcb042d407e69709b9831e4e5a295f","observation_id":"9cf712a0-2da6-4bf7-9953-87b5e763845c","resolution":{"observed_at":"2026-08-05T17:34:03.400026Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-05T17:34:03.121039Z","title":"Adapt or perish: Adaptive sparse transformer with attentive feature refinement for image restoration","venue":null,"work_id":"5c7bde13-47f5-45c5-b256-6fc4cb5bd818","year":2024},"citing_paper":{"arxiv_id":"2508.16089","last_updated":"2025-08-22T04:59:08Z","snapshot_observed_at":"2026-08-09T06:44:04.445337Z","submitted_at":"2025-08-22T04:59:08Z","title":"Two-flow Feedback Multi-scale Progressive Generative Adversarial Network","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-05T17:34:02.534512Z"},"links":{"citing_paper":"/paper/2508.16089"},"observation_digest":"sha256:bd251ff34e021db17da505cece3b597972bc93592c05ac211cb073f2d97c14ac","observation_id":"c953e967-ddb9-49a9-bbe8-26f3ebf106cb","resolution":{"observed_at":"2026-08-05T17:34:03.192686Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+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":"2026-08-05T17:34:02.890154Z","title":"Wdig: a wavelet domain image generation framework based on frequency domain op- timization","venue":null,"work_id":"c7d527ae-db33-41f6-bbd8-8f210091e0e9","year":2023},"citing_paper":{"arxiv_id":"2508.16089","last_updated":"2025-08-22T04:59:08Z","snapshot_observed_at":"2026-08-09T06:44:04.445337Z","submitted_at":"2025-08-22T04:59:08Z","title":"Two-flow Feedback Multi-scale Progressive Generative Adversarial Network","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-05T17:34:02.646497Z"},"links":{"citing_paper":"/paper/2508.16089"},"observation_digest":"sha256:19403832e54c569779d022bab6cea195300020bd31d1458ac03c878749591792","observation_id":"9840be96-bf92-43a3-bbe7-7c1e96ab7293","resolution":{"observed_at":"2026-08-05T17:34:03.004159Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2508.16089","last_updated":"2025-08-22T04:59:08Z","latest_version":1,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-09T06:44:04.445337Z","submitted_at":"2025-08-22T04:59:08Z","title":"Two-flow Feedback Multi-scale Progressive Generative Adversarial Network"},"reference_resolution":{"displayed":32,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":9,"verified_exact":0,"verified_fuzzy":23},"total_outbound_references":32},"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":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"thesis":"As of 9 August 2026, this Paper Citation Record lists 32 of 32 outbound references and 0 inbound Pith citation observations for arXiv:2508.16089."}