{"as_of":"2026-08-19T23:12:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:f5ab2f4bf31204602158dd96db25e2ac76ae8b4b27f957c495548784c7457a8d","coverage":[{"denominator":66,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":66,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-04T04:19:09.392815Z","state":"measured"},{"denominator":66,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":66,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-19T06:32:44.657259+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/2608.02583/citation-record","integrity":"/paper/2608.02583/integrity","json":"/paper/2608.02583/citation-record.json","paper":"/paper/2608.02583"},"outbound":[{"citation":{"cited_paper":{"arxiv_id":"2502.13923","last_updated":"2025-02-19T18:00:14Z","snapshot_observed_at":"2026-08-14T04:17:22.593941Z","submitted_at":"2025-02-19T18:00:14Z","title":"Qwen2.5-VL Technical Report","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2502.13923","snapshot_observed_at":"2026-08-04T04:19:01.126893Z","title":"5-vl technical report , author=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.02583","last_updated":"2026-08-03T17:54:11Z","snapshot_observed_at":"2026-08-12T13:33:06.916298Z","submitted_at":"2026-08-03T17:54:11Z","title":"UEmbed: Unified Sparse and Dense Multimodal Embeddings","version":1},"reference_index":1,"source":"arxiv_source","source_observed_at":"2026-08-04T04:19:01.126893Z"},"links":{"cited_paper":"/paper/2502.13923","citing_paper":"/paper/2608.02583"},"observation_digest":"sha256:374b3bc604cc24220434af7aafcaaf77391bd1191add17db4f7e43585d07deca","observation_id":"b01c1d4b-1f5f-44d1-a69c-f483871cc95b","resolution":{"observed_at":"2026-08-04T04:19:01.126893Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2409.12191","last_updated":"2024-10-03T15:54:49Z","snapshot_observed_at":"2026-08-06T05:35:29.109022Z","submitted_at":"2024-09-18T17:59:32Z","title":"Qwen2-VL: Enhancing Vision-Language Model's Perception of the World at Any Resolution","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2409.12191","snapshot_observed_at":"2026-08-04T04:19:01.236407Z","title":"arXiv preprint arXiv:2409.12191 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.02583","last_updated":"2026-08-03T17:54:11Z","snapshot_observed_at":"2026-08-12T13:33:06.916298Z","submitted_at":"2026-08-03T17:54:11Z","title":"UEmbed: Unified Sparse and Dense Multimodal Embeddings","version":1},"reference_index":2,"source":"arxiv_source","source_observed_at":"2026-08-04T04:19:01.236407Z"},"links":{"cited_paper":"/paper/2409.12191","citing_paper":"/paper/2608.02583"},"observation_digest":"sha256:89709c02d69ad2bb330324ab921461d636a5a6b897c67a42585730eaafb0a935","observation_id":"b23b63e9-f658-4bac-985f-62dbde2e8f45","resolution":{"observed_at":"2026-08-04T04:19:01.236407Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2312.11805","last_updated":"2025-05-09T21:04:06Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-12-19T02:39:27Z","title":"Gemini: A Family of Highly Capable Multimodal Models","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2312.11805","snapshot_observed_at":"2026-08-04T04:19:01.392605Z","title":"arXiv preprint arXiv:2312.11805 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.02583","last_updated":"2026-08-03T17:54:11Z","snapshot_observed_at":"2026-08-12T13:33:06.916298Z","submitted_at":"2026-08-03T17:54:11Z","title":"UEmbed: Unified Sparse and Dense Multimodal Embeddings","version":1},"reference_index":3,"source":"arxiv_source","source_observed_at":"2026-08-04T04:19:01.392605Z"},"links":{"cited_paper":"/paper/2312.11805","citing_paper":"/paper/2608.02583"},"observation_digest":"sha256:551b06a2c79935f19fd8fed41f82d52e0f61d4fc62837d8579012bc5805ad7df","observation_id":"80b010c1-d5b3-4565-a721-5b10d15f0b68","resolution":{"observed_at":"2026-08-04T04:19:01.392605Z","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":"2026-08-04T04:19:01.534857Z","title":"Gemini-2.0 , url =","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.02583","last_updated":"2026-08-03T17:54:11Z","snapshot_observed_at":"2026-08-12T13:33:06.916298Z","submitted_at":"2026-08-03T17:54:11Z","title":"UEmbed: Unified Sparse and Dense Multimodal Embeddings","version":1},"reference_index":4,"source":"arxiv_source","source_observed_at":"2026-08-04T04:19:01.534857Z"},"links":{"citing_paper":"/paper/2608.02583"},"observation_digest":"sha256:cdde8662de28a350aef2ce13e82dd4edc6227f97274f37f58ca89ab457acf83e","observation_id":"beb68027-5581-41e8-8be6-ebc3f64c2fe8","resolution":{"observed_at":"2026-08-04T04:19:01.534857Z","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":"2026-08-04T04:19:01.688508Z","title":"2024 , eprint=","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2608.02583","last_updated":"2026-08-03T17:54:11Z","snapshot_observed_at":"2026-08-12T13:33:06.916298Z","submitted_at":"2026-08-03T17:54:11Z","title":"UEmbed: Unified Sparse and Dense Multimodal Embeddings","version":1},"reference_index":5,"source":"arxiv_source","source_observed_at":"2026-08-04T04:19:01.688508Z"},"links":{"citing_paper":"/paper/2608.02583"},"observation_digest":"sha256:54e4055f33482977e4a58f0c4120311f633b1afd44b9450a36373571941920fb","observation_id":"322747f8-8354-47eb-90e9-3cdf52a76e53","resolution":{"observed_at":"2026-08-04T04:19:01.688508Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2601.03267","last_updated":"2026-05-01T23:55:43Z","snapshot_observed_at":"2026-08-15T00:17:32.875866Z","submitted_at":"2025-12-19T07:05:38Z","title":"OpenAI GPT-5 System Card","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2601.03267","snapshot_observed_at":"2026-08-04T04:19:01.789310Z","title":"arXiv preprint arXiv:2601.03267 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.02583","last_updated":"2026-08-03T17:54:11Z","snapshot_observed_at":"2026-08-12T13:33:06.916298Z","submitted_at":"2026-08-03T17:54:11Z","title":"UEmbed: Unified Sparse and Dense Multimodal Embeddings","version":1},"reference_index":6,"source":"arxiv_source","source_observed_at":"2026-08-04T04:19:01.789310Z"},"links":{"cited_paper":"/paper/2601.03267","citing_paper":"/paper/2608.02583"},"observation_digest":"sha256:293ddb85485c1a7e1fedb51a54cd475b5bce64935a2cdd56dab9aec59ab3c4da","observation_id":"d93be13d-477a-4ae1-9dd1-eb4214c4a151","resolution":{"observed_at":"2026-08-04T04:19:01.789310Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2511.21631","last_updated":"2025-11-27T12:16:54Z","snapshot_observed_at":"2026-08-17T13:26:10.378579Z","submitted_at":"2025-11-26T17:59:08Z","title":"Qwen3-VL Technical Report","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2511.21631","snapshot_observed_at":"2026-08-04T04:19:01.907888Z","title":"arXiv preprint arXiv:2511.21631 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.02583","last_updated":"2026-08-03T17:54:11Z","snapshot_observed_at":"2026-08-12T13:33:06.916298Z","submitted_at":"2026-08-03T17:54:11Z","title":"UEmbed: Unified Sparse and Dense Multimodal Embeddings","version":1},"reference_index":7,"source":"arxiv_source","source_observed_at":"2026-08-04T04:19:01.907888Z"},"links":{"cited_paper":"/paper/2511.21631","citing_paper":"/paper/2608.02583"},"observation_digest":"sha256:dc8510da0d47c3d73509c81cc8350576581e92498ebe4b45b8a2f2b936505c86","observation_id":"0d76be4b-4b71-456c-9ac9-f55108328ef4","resolution":{"observed_at":"2026-08-04T04:19:01.907888Z","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":"2026-08-04T04:19:01.954146Z","title":"2009 , publisher=","venue":null,"work_id":null,"year":2009},"citing_paper":{"arxiv_id":"2608.02583","last_updated":"2026-08-03T17:54:11Z","snapshot_observed_at":"2026-08-12T13:33:06.916298Z","submitted_at":"2026-08-03T17:54:11Z","title":"UEmbed: Unified Sparse and Dense Multimodal Embeddings","version":1},"reference_index":8,"source":"arxiv_source","source_observed_at":"2026-08-04T04:19:01.954146Z"},"links":{"citing_paper":"/paper/2608.02583"},"observation_digest":"sha256:23af13d92b4ecf5ef7060e2368134b550694371f25ca9b2a4ca0f97e2273a1f3","observation_id":"aba5006a-92a3-4d94-bd04-e5db37ddf610","resolution":{"observed_at":"2026-08-04T04:19:01.954146Z","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":"2026-08-04T04:19:02.016814Z","title":"SPLADE: Sparse Lexical and Expansion Model for First Stage Ranking , year =","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.02583","last_updated":"2026-08-03T17:54:11Z","snapshot_observed_at":"2026-08-12T13:33:06.916298Z","submitted_at":"2026-08-03T17:54:11Z","title":"UEmbed: Unified Sparse and Dense Multimodal Embeddings","version":1},"reference_index":9,"source":"arxiv_source","source_observed_at":"2026-08-04T04:19:02.016814Z"},"links":{"citing_paper":"/paper/2608.02583"},"observation_digest":"sha256:10fe8ed97ac0e0d9564dff3e3aa4b7307c07e703504886bb9523cb33cd20b554","observation_id":"7fcd639a-a351-45f3-b20d-94e299fb7fb5","resolution":{"observed_at":"2026-08-04T04:19:02.016814Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2109.10086","last_updated":"2021-09-21T10:43:42Z","snapshot_observed_at":"2026-08-16T17:55:10.471708Z","submitted_at":"2021-09-21T10:43:42Z","title":"SPLADE v2: Sparse Lexical and Expansion Model for Information Retrieval","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2109.10086","snapshot_observed_at":"2026-08-04T04:19:02.179998Z","title":"SPLADE v2: Sparse Lexical and Expansion Model for Information Retrieval , publisher =","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2608.02583","last_updated":"2026-08-03T17:54:11Z","snapshot_observed_at":"2026-08-12T13:33:06.916298Z","submitted_at":"2026-08-03T17:54:11Z","title":"UEmbed: Unified Sparse and Dense Multimodal Embeddings","version":1},"reference_index":10,"source":"arxiv_source","source_observed_at":"2026-08-04T04:19:02.179998Z"},"links":{"cited_paper":"/paper/2109.10086","citing_paper":"/paper/2608.02583"},"observation_digest":"sha256:a50de9d77b671d4056e57d6556c2cb5f6585e127dee365653b719749ffff02c6","observation_id":"5ff339a3-6a3f-4227-8a02-668413527904","resolution":{"observed_at":"2026-08-04T04:19:02.179998Z","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":"2026-08-04T04:19:02.334375Z","title":"From Distillation to Hard Negative Sampling: Making Sparse Neural IR Models More Effective , year =","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.02583","last_updated":"2026-08-03T17:54:11Z","snapshot_observed_at":"2026-08-12T13:33:06.916298Z","submitted_at":"2026-08-03T17:54:11Z","title":"UEmbed: Unified Sparse and Dense Multimodal Embeddings","version":1},"reference_index":11,"source":"arxiv_source","source_observed_at":"2026-08-04T04:19:02.334375Z"},"links":{"citing_paper":"/paper/2608.02583"},"observation_digest":"sha256:4828e33211bd07bbc4fd7a470a20044edfc43cf21d3f2fc657e0accc234becb2","observation_id":"79e3e8bd-e6ce-4635-aa6c-4cc09495ad17","resolution":{"observed_at":"2026-08-04T04:19:02.334375Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2403.06789","last_updated":"2024-03-11T15:04:55Z","snapshot_observed_at":"2026-08-19T22:01:34.768103Z","submitted_at":"2024-03-11T15:04:55Z","title":"SPLADE-v3: New baselines for SPLADE","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2403.06789","snapshot_observed_at":"2026-08-04T04:19:02.502205Z","title":"arXiv preprint arXiv:2403.06789 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.02583","last_updated":"2026-08-03T17:54:11Z","snapshot_observed_at":"2026-08-12T13:33:06.916298Z","submitted_at":"2026-08-03T17:54:11Z","title":"UEmbed: Unified Sparse and Dense Multimodal Embeddings","version":1},"reference_index":12,"source":"arxiv_source","source_observed_at":"2026-08-04T04:19:02.502205Z"},"links":{"cited_paper":"/paper/2403.06789","citing_paper":"/paper/2608.02583"},"observation_digest":"sha256:3687d6841912cfcdb273bcd6275543d9aa4c2ed7211e61c145f6d964247dc1eb","observation_id":"e794e10c-fb9a-49f6-8e4d-8b062caa6375","resolution":{"observed_at":"2026-08-04T04:19:02.502205Z","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":"2026-08-04T04:19:02.737067Z","title":"Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval , pages=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.02583","last_updated":"2026-08-03T17:54:11Z","snapshot_observed_at":"2026-08-12T13:33:06.916298Z","submitted_at":"2026-08-03T17:54:11Z","title":"UEmbed: Unified Sparse and Dense Multimodal Embeddings","version":1},"reference_index":13,"source":"arxiv_source","source_observed_at":"2026-08-04T04:19:02.737067Z"},"links":{"citing_paper":"/paper/2608.02583"},"observation_digest":"sha256:0dc37e7bd2e61a73965bcf6d4b320eb63c81e1693fcfd3317908868e2b83e0f8","observation_id":"37ee768d-7788-4a33-90c4-092855519674","resolution":{"observed_at":"2026-08-04T04:19:02.737067Z","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":"2026-08-04T04:19:02.832353Z","title":"Findings of the Association for Computational Linguistics: EACL 2024 , pages=","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2608.02583","last_updated":"2026-08-03T17:54:11Z","snapshot_observed_at":"2026-08-12T13:33:06.916298Z","submitted_at":"2026-08-03T17:54:11Z","title":"UEmbed: Unified Sparse and Dense Multimodal Embeddings","version":1},"reference_index":14,"source":"arxiv_source","source_observed_at":"2026-08-04T04:19:02.832353Z"},"links":{"citing_paper":"/paper/2608.02583"},"observation_digest":"sha256:53cd2e697de8cbd5f7ac085a7676b0f49cfb9c59151113d9dac38657d1dade50","observation_id":"cdc9e7a3-9bc0-4e20-b5d8-ed146e3a6636","resolution":{"observed_at":"2026-08-04T04:19:02.832353Z","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":"2026-08-04T04:19:02.888469Z","title":"arXiv preprint arXiv:2603.13277 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.02583","last_updated":"2026-08-03T17:54:11Z","snapshot_observed_at":"2026-08-12T13:33:06.916298Z","submitted_at":"2026-08-03T17:54:11Z","title":"UEmbed: Unified Sparse and Dense Multimodal Embeddings","version":1},"reference_index":15,"source":"arxiv_source","source_observed_at":"2026-08-04T04:19:02.888469Z"},"links":{"citing_paper":"/paper/2608.02583"},"observation_digest":"sha256:ff249d24bf2b5ad7b524e86d834a5bffb03b277f69ddcdd390d2acbcb7c3d045","observation_id":"328a6e73-b2f4-4a3a-aa61-5bb393b23c8d","resolution":{"observed_at":"2026-08-04T04:19:02.888469Z","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":"2026-08-04T04:19:02.988976Z","title":"Findings of the association for computational linguistics: ACL 2024 , pages=","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2608.02583","last_updated":"2026-08-03T17:54:11Z","snapshot_observed_at":"2026-08-12T13:33:06.916298Z","submitted_at":"2026-08-03T17:54:11Z","title":"UEmbed: Unified Sparse and Dense Multimodal Embeddings","version":1},"reference_index":16,"source":"arxiv_source","source_observed_at":"2026-08-04T04:19:02.988976Z"},"links":{"citing_paper":"/paper/2608.02583"},"observation_digest":"sha256:b0094eed0a87ed0ddd71ab023e3c71849444fa530ce7e4ef6c28d8270cc73c3f","observation_id":"7db15754-7558-41a5-b5a0-3da92d045415","resolution":{"observed_at":"2026-08-04T04:19:02.988976Z","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":"2026-08-04T04:19:03.056297Z","title":"arXiv preprint arXiv:2601.01684 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.02583","last_updated":"2026-08-03T17:54:11Z","snapshot_observed_at":"2026-08-12T13:33:06.916298Z","submitted_at":"2026-08-03T17:54:11Z","title":"UEmbed: Unified Sparse and Dense Multimodal Embeddings","version":1},"reference_index":17,"source":"arxiv_source","source_observed_at":"2026-08-04T04:19:03.056297Z"},"links":{"citing_paper":"/paper/2608.02583"},"observation_digest":"sha256:3ad0a24e8abae5b873b7bcbfd75b6a88adcc3863d8788a3d143b709c9d3e45df","observation_id":"50784fde-32fd-433d-b283-84f65366836e","resolution":{"observed_at":"2026-08-04T04:19:03.056297Z","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":"2026-08-04T04:19:03.222377Z","title":"Proceedings of the 45th international ACM SIGIR conference on research and development in information retrieval , pages=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.02583","last_updated":"2026-08-03T17:54:11Z","snapshot_observed_at":"2026-08-12T13:33:06.916298Z","submitted_at":"2026-08-03T17:54:11Z","title":"UEmbed: Unified Sparse and Dense Multimodal Embeddings","version":1},"reference_index":18,"source":"arxiv_source","source_observed_at":"2026-08-04T04:19:03.222377Z"},"links":{"citing_paper":"/paper/2608.02583"},"observation_digest":"sha256:ada78e80df24ecb3b29b286ab0ca87385264f289e9923bfb7717f065b6fd930f","observation_id":"83ffb7b0-770d-40ef-a1d2-2f7877430971","resolution":{"observed_at":"2026-08-04T04:19:03.222377Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2404.05961","last_updated":"2024-08-21T22:46:05Z","snapshot_observed_at":"2026-08-16T14:02:33.067745Z","submitted_at":"2024-04-09T02:51:05Z","title":"LLM2Vec: Large Language Models Are Secretly Powerful Text Encoders","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.05961","snapshot_observed_at":"2026-08-04T04:19:03.277837Z","title":"arXiv preprint arXiv:2404.05961 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.02583","last_updated":"2026-08-03T17:54:11Z","snapshot_observed_at":"2026-08-12T13:33:06.916298Z","submitted_at":"2026-08-03T17:54:11Z","title":"UEmbed: Unified Sparse and Dense Multimodal Embeddings","version":1},"reference_index":19,"source":"arxiv_source","source_observed_at":"2026-08-04T04:19:03.277837Z"},"links":{"cited_paper":"/paper/2404.05961","citing_paper":"/paper/2608.02583"},"observation_digest":"sha256:08e79c3930c4fa1078239d9a0e5e49c8d7058f8adf219d90ed863aa61979fd6e","observation_id":"a82fee4b-0c81-4b1a-8cdb-cab852480563","resolution":{"observed_at":"2026-08-04T04:19:03.277837Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2408.11119","last_updated":"2024-08-22T03:46:25Z","snapshot_observed_at":"2026-08-19T02:46:17.586896Z","submitted_at":"2024-08-20T18:21:54Z","title":"Mistral-SPLADE: LLMs for better Learned Sparse Retrieval","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2408.11119","snapshot_observed_at":"2026-08-04T04:19:03.337415Z","title":"arXiv preprint arXiv:2408.11119 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.02583","last_updated":"2026-08-03T17:54:11Z","snapshot_observed_at":"2026-08-12T13:33:06.916298Z","submitted_at":"2026-08-03T17:54:11Z","title":"UEmbed: Unified Sparse and Dense Multimodal Embeddings","version":1},"reference_index":20,"source":"arxiv_source","source_observed_at":"2026-08-04T04:19:03.337415Z"},"links":{"cited_paper":"/paper/2408.11119","citing_paper":"/paper/2608.02583"},"observation_digest":"sha256:b5fc679042c68b91d155cbf724b12448e2cf2d1550fa34e13abda17bca843a9d","observation_id":"b0d95e01-d41d-4be3-ad23-f34c5b85205a","resolution":{"observed_at":"2026-08-04T04:19:03.337415Z","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":"2026-08-04T04:19:03.435649Z","title":"European Conference on Information Retrieval , pages=","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2608.02583","last_updated":"2026-08-03T17:54:11Z","snapshot_observed_at":"2026-08-12T13:33:06.916298Z","submitted_at":"2026-08-03T17:54:11Z","title":"UEmbed: Unified Sparse and Dense Multimodal Embeddings","version":1},"reference_index":21,"source":"arxiv_source","source_observed_at":"2026-08-04T04:19:03.435649Z"},"links":{"citing_paper":"/paper/2608.02583"},"observation_digest":"sha256:00c20395bd0a00e075e9e5de9927ccc5cd2e2585b41b9f500cc4586ebc6bbebb","observation_id":"bb5300ff-c754-47cb-98db-2fe716a94ace","resolution":{"observed_at":"2026-08-04T04:19:03.435649Z","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":"2026-08-04T04:19:03.547970Z","title":"Proceedings of the 34th ACM International Conference on Information and Knowledge Management , pages=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.02583","last_updated":"2026-08-03T17:54:11Z","snapshot_observed_at":"2026-08-12T13:33:06.916298Z","submitted_at":"2026-08-03T17:54:11Z","title":"UEmbed: Unified Sparse and Dense Multimodal Embeddings","version":1},"reference_index":22,"source":"arxiv_source","source_observed_at":"2026-08-04T04:19:03.547970Z"},"links":{"citing_paper":"/paper/2608.02583"},"observation_digest":"sha256:19d0c5f7a5190e2a11e8d80c63a3aec9b2877d6a6210300eeb95bc82e860ffc5","observation_id":"f03d3e2a-bae9-4c92-ba65-33b8dc1a6594","resolution":{"observed_at":"2026-08-04T04:19:03.547970Z","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":"2026-08-04T04:19:03.653020Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.02583","last_updated":"2026-08-03T17:54:11Z","snapshot_observed_at":"2026-08-12T13:33:06.916298Z","submitted_at":"2026-08-03T17:54:11Z","title":"UEmbed: Unified Sparse and Dense Multimodal Embeddings","version":1},"reference_index":23,"source":"arxiv_source","source_observed_at":"2026-08-04T04:19:03.653020Z"},"links":{"citing_paper":"/paper/2608.02583"},"observation_digest":"sha256:d4b7963c868191e59c016982f55c534d758e167e66a823b2efdc0cb1dc4bc86c","observation_id":"f950cd86-3583-4aab-ae25-56901c44aa23","resolution":{"observed_at":"2026-08-04T04:19:03.653020Z","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":"2026-08-04T04:19:03.762458Z","title":"Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing , pages=","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2608.02583","last_updated":"2026-08-03T17:54:11Z","snapshot_observed_at":"2026-08-12T13:33:06.916298Z","submitted_at":"2026-08-03T17:54:11Z","title":"UEmbed: Unified Sparse and Dense Multimodal Embeddings","version":1},"reference_index":24,"source":"arxiv_source","source_observed_at":"2026-08-04T04:19:03.762458Z"},"links":{"citing_paper":"/paper/2608.02583"},"observation_digest":"sha256:f85efee3e1ad631cea2a77e5638837e2c092a923ddabadfd5172fa98bca753f1","observation_id":"efdab258-7aa3-4967-ac4a-3dc8d8960e30","resolution":{"observed_at":"2026-08-04T04:19:03.762458Z","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":"2026-08-04T04:19:03.840791Z","title":"Advances in neural information processing systems , volume=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.02583","last_updated":"2026-08-03T17:54:11Z","snapshot_observed_at":"2026-08-12T13:33:06.916298Z","submitted_at":"2026-08-03T17:54:11Z","title":"UEmbed: Unified Sparse and Dense Multimodal Embeddings","version":1},"reference_index":25,"source":"arxiv_source","source_observed_at":"2026-08-04T04:19:03.840791Z"},"links":{"citing_paper":"/paper/2608.02583"},"observation_digest":"sha256:f83f74b142e84682d5aa3e6f45aab0cde6849ace9be181a19215d8840d3c4ba7","observation_id":"383230a9-2e78-4580-90c7-4e6faa1855e3","resolution":{"observed_at":"2026-08-04T04:19:03.840791Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"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":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2111.02114","snapshot_observed_at":"2026-08-04T04:19:03.997120Z","title":"arXiv preprint arXiv:2111.02114 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.02583","last_updated":"2026-08-03T17:54:11Z","snapshot_observed_at":"2026-08-12T13:33:06.916298Z","submitted_at":"2026-08-03T17:54:11Z","title":"UEmbed: Unified Sparse and Dense Multimodal Embeddings","version":1},"reference_index":26,"source":"arxiv_source","source_observed_at":"2026-08-04T04:19:03.997120Z"},"links":{"cited_paper":"/paper/2111.02114","citing_paper":"/paper/2608.02583"},"observation_digest":"sha256:a0b2042526aee1f676d4e69e1a121201d45cada4a346d9fa117bf2625aaecb51","observation_id":"54015a78-060a-4092-b1bf-57572dcffb41","resolution":{"observed_at":"2026-08-04T04:19:03.997120Z","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":"2026-08-04T04:19:04.083039Z","title":"Computer Vision--ECCV 2014: 13th European Conference, Zurich, Switzerland, September 6-12, 2014, Proceedings, Part V 13 , pages=","venue":null,"work_id":null,"year":2014},"citing_paper":{"arxiv_id":"2608.02583","last_updated":"2026-08-03T17:54:11Z","snapshot_observed_at":"2026-08-12T13:33:06.916298Z","submitted_at":"2026-08-03T17:54:11Z","title":"UEmbed: Unified Sparse and Dense Multimodal Embeddings","version":1},"reference_index":27,"source":"arxiv_source","source_observed_at":"2026-08-04T04:19:04.083039Z"},"links":{"citing_paper":"/paper/2608.02583"},"observation_digest":"sha256:889fd0c05e34c98c0f4e3d82ef1daea8df06e946192b0419f80c0e1ef662e467","observation_id":"f8af3b21-9eae-4107-88bc-eba251062b86","resolution":{"observed_at":"2026-08-04T04:19:04.083039Z","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":"2026-08-04T04:19:04.252997Z","title":"Proceedings of the IEEE international conference on computer vision , pages=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.02583","last_updated":"2026-08-03T17:54:11Z","snapshot_observed_at":"2026-08-12T13:33:06.916298Z","submitted_at":"2026-08-03T17:54:11Z","title":"UEmbed: Unified Sparse and Dense Multimodal Embeddings","version":1},"reference_index":28,"source":"arxiv_source","source_observed_at":"2026-08-04T04:19:04.252997Z"},"links":{"citing_paper":"/paper/2608.02583"},"observation_digest":"sha256:f06381e9b0365fa663b702ce70c67c0e9e193414bbcac42ab09ff58cfe2fa288","observation_id":"3ac1c712-6d42-4d6a-9e56-48c7be0c6f95","resolution":{"observed_at":"2026-08-04T04:19:04.252997Z","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":"2026-08-04T04:19:04.290121Z","title":null,"venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2608.02583","last_updated":"2026-08-03T17:54:11Z","snapshot_observed_at":"2026-08-12T13:33:06.916298Z","submitted_at":"2026-08-03T17:54:11Z","title":"UEmbed: Unified Sparse and Dense Multimodal Embeddings","version":1},"reference_index":29,"source":"arxiv_source","source_observed_at":"2026-08-04T04:19:04.290121Z"},"links":{"citing_paper":"/paper/2608.02583"},"observation_digest":"sha256:bf2945e510b3f42e21ba6d1e01f289b7c78eee9f5a605221e3d5c286e8bf2728","observation_id":"6e2e6ed8-e3d1-4c38-9626-605640ecf86d","resolution":{"observed_at":"2026-08-04T04:19:04.290121Z","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":"2026-08-04T04:19:04.390302Z","title":"International Conference on Learning Representations , volume=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.02583","last_updated":"2026-08-03T17:54:11Z","snapshot_observed_at":"2026-08-12T13:33:06.916298Z","submitted_at":"2026-08-03T17:54:11Z","title":"UEmbed: Unified Sparse and Dense Multimodal Embeddings","version":1},"reference_index":30,"source":"arxiv_source","source_observed_at":"2026-08-04T04:19:04.390302Z"},"links":{"citing_paper":"/paper/2608.02583"},"observation_digest":"sha256:b4408a221951bb9a798f0ef5b474e380243259326115b64d94a5037705473f4a","observation_id":"8a702b57-4668-439f-912a-e35143d72d2b","resolution":{"observed_at":"2026-08-04T04:19:04.390302Z","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":"2026-08-04T04:19:04.468419Z","title":"International Conference on Learning Representations , volume=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.02583","last_updated":"2026-08-03T17:54:11Z","snapshot_observed_at":"2026-08-12T13:33:06.916298Z","submitted_at":"2026-08-03T17:54:11Z","title":"UEmbed: Unified Sparse and Dense Multimodal Embeddings","version":1},"reference_index":31,"source":"arxiv_source","source_observed_at":"2026-08-04T04:19:04.468419Z"},"links":{"citing_paper":"/paper/2608.02583"},"observation_digest":"sha256:20dc55b27591940c9c1690eb2c09948907491a82404edcd711146d4d2284e2f3","observation_id":"1b360777-fac5-4b02-9607-3447fed712cd","resolution":{"observed_at":"2026-08-04T04:19:04.468419Z","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":"2026-08-04T04:19:04.629834Z","title":"2025 , url=","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2608.02583","last_updated":"2026-08-03T17:54:11Z","snapshot_observed_at":"2026-08-12T13:33:06.916298Z","submitted_at":"2026-08-03T17:54:11Z","title":"UEmbed: Unified Sparse and Dense Multimodal Embeddings","version":1},"reference_index":32,"source":"arxiv_source","source_observed_at":"2026-08-04T04:19:04.629834Z"},"links":{"citing_paper":"/paper/2608.02583"},"observation_digest":"sha256:2cab41f93f32ebbeeac03b054ae11ec236c286b88fb925c33819a30da3d211bb","observation_id":"1421ea3d-b2a0-416f-bf73-4b67e90f5d4c","resolution":{"observed_at":"2026-08-04T04:19:04.629834Z","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":"2026-08-04T04:19:04.739673Z","title":"2025 , url=","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2608.02583","last_updated":"2026-08-03T17:54:11Z","snapshot_observed_at":"2026-08-12T13:33:06.916298Z","submitted_at":"2026-08-03T17:54:11Z","title":"UEmbed: Unified Sparse and Dense Multimodal Embeddings","version":1},"reference_index":33,"source":"arxiv_source","source_observed_at":"2026-08-04T04:19:04.739673Z"},"links":{"citing_paper":"/paper/2608.02583"},"observation_digest":"sha256:122290d51e319138c4b408df63e0b64b620a5a58b0fb12d2bf64fc83f431d78f","observation_id":"72383cf4-b75d-4e7d-82ab-70054fc891ac","resolution":{"observed_at":"2026-08-04T04:19:04.739673Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2402.14334","last_updated":"2024-02-22T06:59:50Z","snapshot_observed_at":"2026-08-16T14:16:20.951147Z","submitted_at":"2024-02-22T06:59:50Z","title":"INSTRUCTIR: A Benchmark for Instruction Following of Information Retrieval Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.14334","snapshot_observed_at":"2026-08-04T04:19:04.821659Z","title":"arXiv preprint arXiv:2402.14334 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.02583","last_updated":"2026-08-03T17:54:11Z","snapshot_observed_at":"2026-08-12T13:33:06.916298Z","submitted_at":"2026-08-03T17:54:11Z","title":"UEmbed: Unified Sparse and Dense Multimodal Embeddings","version":1},"reference_index":34,"source":"arxiv_source","source_observed_at":"2026-08-04T04:19:04.821659Z"},"links":{"cited_paper":"/paper/2402.14334","citing_paper":"/paper/2608.02583"},"observation_digest":"sha256:c867383119f4305a456401e6ecadd06e01d802f6d629787322af6250f454f745","observation_id":"4b27a94d-aa92-4634-b2c8-81fba53188f0","resolution":{"observed_at":"2026-08-04T04:19:04.821659Z","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":"2026-08-04T04:19:04.953842Z","title":"2026 , eprint=","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2608.02583","last_updated":"2026-08-03T17:54:11Z","snapshot_observed_at":"2026-08-12T13:33:06.916298Z","submitted_at":"2026-08-03T17:54:11Z","title":"UEmbed: Unified Sparse and Dense Multimodal Embeddings","version":1},"reference_index":35,"source":"arxiv_source","source_observed_at":"2026-08-04T04:19:04.953842Z"},"links":{"citing_paper":"/paper/2608.02583"},"observation_digest":"sha256:dc6aab8f181d51a02707743c0ff390f5c40b5848cf0d141124abf3613896acb3","observation_id":"38c7ab89-6931-4d82-b28f-1f6f57e09ace","resolution":{"observed_at":"2026-08-04T04:19:04.953842Z","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":"2026-08-04T04:19:05.105739Z","title":"The Thirty-ninth Annual Conference on Neural Information Processing Systems Datasets and Benchmarks Track , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.02583","last_updated":"2026-08-03T17:54:11Z","snapshot_observed_at":"2026-08-12T13:33:06.916298Z","submitted_at":"2026-08-03T17:54:11Z","title":"UEmbed: Unified Sparse and Dense Multimodal Embeddings","version":1},"reference_index":36,"source":"arxiv_source","source_observed_at":"2026-08-04T04:19:05.105739Z"},"links":{"citing_paper":"/paper/2608.02583"},"observation_digest":"sha256:6457259c0c7073ef483bf228343b312d537030e9b97854341dfb3ffc36e70ec5","observation_id":"f133c45b-0f73-4823-bb7b-d074950c3714","resolution":{"observed_at":"2026-08-04T04:19:05.105739Z","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":"2026-08-04T04:19:05.230139Z","title":"Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.02583","last_updated":"2026-08-03T17:54:11Z","snapshot_observed_at":"2026-08-12T13:33:06.916298Z","submitted_at":"2026-08-03T17:54:11Z","title":"UEmbed: Unified Sparse and Dense Multimodal Embeddings","version":1},"reference_index":37,"source":"arxiv_source","source_observed_at":"2026-08-04T04:19:05.230139Z"},"links":{"citing_paper":"/paper/2608.02583"},"observation_digest":"sha256:eec1d23b2a02753d2726a298c5aa5a09a31af8ab4bd07a8f24498dc3532260c7","observation_id":"013c1251-0dbd-4d73-8e39-16a59dce50e5","resolution":{"observed_at":"2026-08-04T04:19:05.230139Z","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":"2026-08-04T04:19:05.378431Z","title":"Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 2) , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.02583","last_updated":"2026-08-03T17:54:11Z","snapshot_observed_at":"2026-08-12T13:33:06.916298Z","submitted_at":"2026-08-03T17:54:11Z","title":"UEmbed: Unified Sparse and Dense Multimodal Embeddings","version":1},"reference_index":38,"source":"arxiv_source","source_observed_at":"2026-08-04T04:19:05.378431Z"},"links":{"citing_paper":"/paper/2608.02583"},"observation_digest":"sha256:20a7789a38e0828b1644c5aa4f6a3258c017c766e6c0101450553b917bd6a352","observation_id":"d00fde92-7401-4785-af80-4537cc3ed811","resolution":{"observed_at":"2026-08-04T04:19:05.378431Z","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":"2026-08-04T04:19:05.555163Z","title":"Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics , pages=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.02583","last_updated":"2026-08-03T17:54:11Z","snapshot_observed_at":"2026-08-12T13:33:06.916298Z","submitted_at":"2026-08-03T17:54:11Z","title":"UEmbed: Unified Sparse and Dense Multimodal Embeddings","version":1},"reference_index":39,"source":"arxiv_source","source_observed_at":"2026-08-04T04:19:05.555163Z"},"links":{"citing_paper":"/paper/2608.02583"},"observation_digest":"sha256:7bdc6258d0f2007cb563ef6a9af951315d7a6816da8d2dac9756c94d68b0cd8e","observation_id":"cc62c46b-1206-46aa-8d52-f424fcd53a02","resolution":{"observed_at":"2026-08-04T04:19:05.555163Z","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":"2026-08-04T04:19:05.758364Z","title":"ArXiv , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.02583","last_updated":"2026-08-03T17:54:11Z","snapshot_observed_at":"2026-08-12T13:33:06.916298Z","submitted_at":"2026-08-03T17:54:11Z","title":"UEmbed: Unified Sparse and Dense Multimodal Embeddings","version":1},"reference_index":40,"source":"arxiv_source","source_observed_at":"2026-08-04T04:19:05.758364Z"},"links":{"citing_paper":"/paper/2608.02583"},"observation_digest":"sha256:b5d34579699b895bf493c70f9c9cd2a5211318cfc027cb3191f6230caff692c2","observation_id":"dbe00272-0040-4c14-aaa7-c3622e76be5a","resolution":{"observed_at":"2026-08-04T04:19:05.758364Z","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":"2026-08-04T04:19:05.977420Z","title":"Proceedings of the 33rd ACM International Conference on Multimedia , pages=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.02583","last_updated":"2026-08-03T17:54:11Z","snapshot_observed_at":"2026-08-12T13:33:06.916298Z","submitted_at":"2026-08-03T17:54:11Z","title":"UEmbed: Unified Sparse and Dense Multimodal Embeddings","version":1},"reference_index":41,"source":"arxiv_source","source_observed_at":"2026-08-04T04:19:05.977420Z"},"links":{"citing_paper":"/paper/2608.02583"},"observation_digest":"sha256:608799fab18fbf517cbb1458ed57d9752ccc01a07d6c12f60941e770309d114e","observation_id":"5db074dc-bd51-4e70-bfba-08bf5ace1e0c","resolution":{"observed_at":"2026-08-04T04:19:05.977420Z","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":"2026-08-04T04:19:06.183940Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.02583","last_updated":"2026-08-03T17:54:11Z","snapshot_observed_at":"2026-08-12T13:33:06.916298Z","submitted_at":"2026-08-03T17:54:11Z","title":"UEmbed: Unified Sparse and Dense Multimodal Embeddings","version":1},"reference_index":42,"source":"arxiv_source","source_observed_at":"2026-08-04T04:19:06.183940Z"},"links":{"citing_paper":"/paper/2608.02583"},"observation_digest":"sha256:1912f8e991d754055a32fcd3d9add395f0e66d7409408782ad9cebe190895e9c","observation_id":"3d96e54f-0fc2-435f-b48b-b22220bea24f","resolution":{"observed_at":"2026-08-04T04:19:06.183940Z","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":"2026-08-04T04:19:06.336343Z","title":"arXiv preprint arXiv:2510.05014 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.02583","last_updated":"2026-08-03T17:54:11Z","snapshot_observed_at":"2026-08-12T13:33:06.916298Z","submitted_at":"2026-08-03T17:54:11Z","title":"UEmbed: Unified Sparse and Dense Multimodal Embeddings","version":1},"reference_index":43,"source":"arxiv_source","source_observed_at":"2026-08-04T04:19:06.336343Z"},"links":{"citing_paper":"/paper/2608.02583"},"observation_digest":"sha256:3e40e7fbad57e15b9aef383c4cb7c74d89397b40ca7f3938e10472794b7c05bb","observation_id":"e5766f71-407d-4ec2-a43c-687441b2875f","resolution":{"observed_at":"2026-08-04T04:19:06.336343Z","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":"2026-08-04T04:19:06.536045Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.02583","last_updated":"2026-08-03T17:54:11Z","snapshot_observed_at":"2026-08-12T13:33:06.916298Z","submitted_at":"2026-08-03T17:54:11Z","title":"UEmbed: Unified Sparse and Dense Multimodal Embeddings","version":1},"reference_index":44,"source":"arxiv_source","source_observed_at":"2026-08-04T04:19:06.536045Z"},"links":{"citing_paper":"/paper/2608.02583"},"observation_digest":"sha256:f12ce8400007a2b0fed0f87ec83653fcfb99e3b2b10907de8bd9c541ac5e2130","observation_id":"87c58519-a358-4e8a-a35e-44df8b4540c3","resolution":{"observed_at":"2026-08-04T04:19:06.536045Z","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":"2026-08-04T04:19:06.600738Z","title":"Findings of the Association for Computational Linguistics: ACL 2025 , pages=","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2608.02583","last_updated":"2026-08-03T17:54:11Z","snapshot_observed_at":"2026-08-12T13:33:06.916298Z","submitted_at":"2026-08-03T17:54:11Z","title":"UEmbed: Unified Sparse and Dense Multimodal Embeddings","version":1},"reference_index":45,"source":"arxiv_source","source_observed_at":"2026-08-04T04:19:06.600738Z"},"links":{"citing_paper":"/paper/2608.02583"},"observation_digest":"sha256:0f26b2af176a8254fc98f5beae44e4b597767f2d1d9c8b55e6c073f9a6845374","observation_id":"26bdf20d-2748-470c-aafa-8ed8a12a3aab","resolution":{"observed_at":"2026-08-04T04:19:06.600738Z","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":"2026-08-04T04:19:06.708190Z","title":"arXiv preprint arXiv:2507.14902 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.02583","last_updated":"2026-08-03T17:54:11Z","snapshot_observed_at":"2026-08-12T13:33:06.916298Z","submitted_at":"2026-08-03T17:54:11Z","title":"UEmbed: Unified Sparse and Dense Multimodal Embeddings","version":1},"reference_index":46,"source":"arxiv_source","source_observed_at":"2026-08-04T04:19:06.708190Z"},"links":{"citing_paper":"/paper/2608.02583"},"observation_digest":"sha256:9f3cafb10afe4076c0fc01ff91d0e084e1ceae892abc4dc0914e7343d9a86143","observation_id":"6ce270de-81db-4f9a-8d34-333b1b2d3e6a","resolution":{"observed_at":"2026-08-04T04:19:06.708190Z","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":"2026-08-04T04:19:06.806071Z","title":"The Thirteenth International Conference on Learning Representations , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.02583","last_updated":"2026-08-03T17:54:11Z","snapshot_observed_at":"2026-08-12T13:33:06.916298Z","submitted_at":"2026-08-03T17:54:11Z","title":"UEmbed: Unified Sparse and Dense Multimodal Embeddings","version":1},"reference_index":47,"source":"arxiv_source","source_observed_at":"2026-08-04T04:19:06.806071Z"},"links":{"citing_paper":"/paper/2608.02583"},"observation_digest":"sha256:708bd9c2cb66cfae0213a6b9b7c340b77ac5495d57ed6e7f44ef03bb7519a6c5","observation_id":"82e6c0e6-4790-4680-a76d-beee2366327d","resolution":{"observed_at":"2026-08-04T04:19:06.806071Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2507.04590","last_updated":"2025-07-07T00:51:57Z","snapshot_observed_at":"2026-08-08T15:48:31.665148Z","submitted_at":"2025-07-07T00:51:57Z","title":"VLM2Vec-V2: Advancing Multimodal Embedding for Videos, Images, and Visual Documents","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2507.04590","snapshot_observed_at":"2026-08-04T04:19:06.867593Z","title":"arXiv preprint arXiv:2507.04590 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.02583","last_updated":"2026-08-03T17:54:11Z","snapshot_observed_at":"2026-08-12T13:33:06.916298Z","submitted_at":"2026-08-03T17:54:11Z","title":"UEmbed: Unified Sparse and Dense Multimodal Embeddings","version":1},"reference_index":48,"source":"arxiv_source","source_observed_at":"2026-08-04T04:19:06.867593Z"},"links":{"cited_paper":"/paper/2507.04590","citing_paper":"/paper/2608.02583"},"observation_digest":"sha256:62ab230bfdc66ad39a70badc68e0a47bf7c4e71dff342148fb4f9a7ea59ce6fd","observation_id":"8bee1823-70d8-4b50-a0f0-749ae245ac30","resolution":{"observed_at":"2026-08-04T04:19:06.867593Z","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":"2026-08-04T04:19:07.034776Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.02583","last_updated":"2026-08-03T17:54:11Z","snapshot_observed_at":"2026-08-12T13:33:06.916298Z","submitted_at":"2026-08-03T17:54:11Z","title":"UEmbed: Unified Sparse and Dense Multimodal Embeddings","version":1},"reference_index":49,"source":"arxiv_source","source_observed_at":"2026-08-04T04:19:07.034776Z"},"links":{"citing_paper":"/paper/2608.02583"},"observation_digest":"sha256:525a6ee9cfdd97eacb11335e0665cec70d00d6775f210ec2081edeaf5a6ae882","observation_id":"e20ec7fa-a5e4-49a5-8318-11cd57b85c1d","resolution":{"observed_at":"2026-08-04T04:19:07.034776Z","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":"2026-08-04T04:19:07.230910Z","title":"arXiv preprint arXiv:2510.27571 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.02583","last_updated":"2026-08-03T17:54:11Z","snapshot_observed_at":"2026-08-12T13:33:06.916298Z","submitted_at":"2026-08-03T17:54:11Z","title":"UEmbed: Unified Sparse and Dense Multimodal Embeddings","version":1},"reference_index":50,"source":"arxiv_source","source_observed_at":"2026-08-04T04:19:07.230910Z"},"links":{"citing_paper":"/paper/2608.02583"},"observation_digest":"sha256:208fb335eeba84886ca4d18f3befe8ca2d8d354e5d4a4b2324cc17a2d7db750e","observation_id":"10bc919f-4bcc-4005-9a33-2bb45b9367ce","resolution":{"observed_at":"2026-08-04T04:19:07.230910Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2601.04720","last_updated":"2026-01-19T09:03:26Z","snapshot_observed_at":"2026-08-14T12:22:57.900954Z","submitted_at":"2026-01-08T08:36:06Z","title":"Qwen3-VL-Embedding and Qwen3-VL-Reranker: A Unified Framework for State-of-the-Art Multimodal Retrieval and Ranking","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2601.04720","snapshot_observed_at":"2026-08-04T04:19:07.332252Z","title":"arXiv preprint arXiv:2601.04720 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.02583","last_updated":"2026-08-03T17:54:11Z","snapshot_observed_at":"2026-08-12T13:33:06.916298Z","submitted_at":"2026-08-03T17:54:11Z","title":"UEmbed: Unified Sparse and Dense Multimodal Embeddings","version":1},"reference_index":51,"source":"arxiv_source","source_observed_at":"2026-08-04T04:19:07.332252Z"},"links":{"cited_paper":"/paper/2601.04720","citing_paper":"/paper/2608.02583"},"observation_digest":"sha256:f578e52be46d8da6d9208ad81fd97329ff0dc5ab741c9cf3a0babf2799bb2933","observation_id":"da127aef-5da0-49ec-b1f8-a19ccb7152c0","resolution":{"observed_at":"2026-08-04T04:19:07.332252Z","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":"2026-08-04T04:19:07.468774Z","title":"arXiv preprint arXiv:2510.27350 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.02583","last_updated":"2026-08-03T17:54:11Z","snapshot_observed_at":"2026-08-12T13:33:06.916298Z","submitted_at":"2026-08-03T17:54:11Z","title":"UEmbed: Unified Sparse and Dense Multimodal Embeddings","version":1},"reference_index":52,"source":"arxiv_source","source_observed_at":"2026-08-04T04:19:07.468774Z"},"links":{"citing_paper":"/paper/2608.02583"},"observation_digest":"sha256:f37ac76470dd7e3612744e6db283ef8b97e32446b3ae196a27cdc862bb559b13","observation_id":"2f46555f-7ae0-4f3d-825b-3bbb6f8e9226","resolution":{"observed_at":"2026-08-04T04:19:07.468774Z","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":"2026-08-04T04:19:07.622303Z","title":"arXiv preprint arXiv:2602.13823 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.02583","last_updated":"2026-08-03T17:54:11Z","snapshot_observed_at":"2026-08-12T13:33:06.916298Z","submitted_at":"2026-08-03T17:54:11Z","title":"UEmbed: Unified Sparse and Dense Multimodal Embeddings","version":1},"reference_index":53,"source":"arxiv_source","source_observed_at":"2026-08-04T04:19:07.622303Z"},"links":{"citing_paper":"/paper/2608.02583"},"observation_digest":"sha256:557cd43c7d46e2a08a6c866aa6cdfc8ebf24680bba961f8b175ffc7220fb2c25","observation_id":"fffe8ba5-cbee-456a-b77e-93bbc29e4810","resolution":{"observed_at":"2026-08-04T04:19:07.622303Z","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":"2026-08-04T04:19:07.707646Z","title":"Findings of the Association for Computational Linguistics: ACL 2023 , pages=","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2608.02583","last_updated":"2026-08-03T17:54:11Z","snapshot_observed_at":"2026-08-12T13:33:06.916298Z","submitted_at":"2026-08-03T17:54:11Z","title":"UEmbed: Unified Sparse and Dense Multimodal Embeddings","version":1},"reference_index":54,"source":"arxiv_source","source_observed_at":"2026-08-04T04:19:07.707646Z"},"links":{"citing_paper":"/paper/2608.02583"},"observation_digest":"sha256:a23091c3204f23cc0ac28fb6c98af5da58d1bc93bee881b8b873314ce53ec703","observation_id":"e92f4674-ce18-464b-9af1-9ceefea1ed46","resolution":{"observed_at":"2026-08-04T04:19:07.707646Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2401.00368","last_updated":"2024-05-31T07:22:01Z","snapshot_observed_at":"2026-08-16T14:30:41.754354Z","submitted_at":"2023-12-31T02:13:18Z","title":"Improving Text Embeddings with Large Language Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2401.00368","snapshot_observed_at":"2026-08-04T04:19:07.893305Z","title":"arXiv preprint arXiv:2401.00368 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.02583","last_updated":"2026-08-03T17:54:11Z","snapshot_observed_at":"2026-08-12T13:33:06.916298Z","submitted_at":"2026-08-03T17:54:11Z","title":"UEmbed: Unified Sparse and Dense Multimodal Embeddings","version":1},"reference_index":55,"source":"arxiv_source","source_observed_at":"2026-08-04T04:19:07.893305Z"},"links":{"cited_paper":"/paper/2401.00368","citing_paper":"/paper/2608.02583"},"observation_digest":"sha256:8f3de3b01c12882df0cb9b256fa33dc04be62ad092bf58d89cb376f4b3449f1d","observation_id":"550e170d-c590-49c9-ab64-5dfa8ab8750d","resolution":{"observed_at":"2026-08-04T04:19:07.893305Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2402.09906","last_updated":"2025-03-03T04:28:49Z","snapshot_observed_at":"2026-08-17T08:29:24.619960Z","submitted_at":"2024-02-15T12:12:19Z","title":"Generative Representational Instruction Tuning","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.09906","snapshot_observed_at":"2026-08-04T04:19:08.011532Z","title":"arXiv preprint arXiv:2402.09906 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.02583","last_updated":"2026-08-03T17:54:11Z","snapshot_observed_at":"2026-08-12T13:33:06.916298Z","submitted_at":"2026-08-03T17:54:11Z","title":"UEmbed: Unified Sparse and Dense Multimodal Embeddings","version":1},"reference_index":56,"source":"arxiv_source","source_observed_at":"2026-08-04T04:19:08.011532Z"},"links":{"cited_paper":"/paper/2402.09906","citing_paper":"/paper/2608.02583"},"observation_digest":"sha256:8e0eaa403caebbf03177c788386f39542a0aeb2a8692d433e6121d11c16263a0","observation_id":"f59ab6dc-9114-4b71-9702-e4485b31e1b0","resolution":{"observed_at":"2026-08-04T04:19:08.011532Z","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":"2026-08-04T04:19:08.091958Z","title":"International Conference on Learning Representations , volume=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.02583","last_updated":"2026-08-03T17:54:11Z","snapshot_observed_at":"2026-08-12T13:33:06.916298Z","submitted_at":"2026-08-03T17:54:11Z","title":"UEmbed: Unified Sparse and Dense Multimodal Embeddings","version":1},"reference_index":57,"source":"arxiv_source","source_observed_at":"2026-08-04T04:19:08.091958Z"},"links":{"citing_paper":"/paper/2608.02583"},"observation_digest":"sha256:39f7d6edf9d6665f1f12d8ef8714634db4916b8db668fc954b12549801598118","observation_id":"0e17ad53-f814-4577-810b-2c6a9918b7e9","resolution":{"observed_at":"2026-08-04T04:19:08.091958Z","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":"2026-08-04T04:19:08.249375Z","title":"2025 , url =","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2608.02583","last_updated":"2026-08-03T17:54:11Z","snapshot_observed_at":"2026-08-12T13:33:06.916298Z","submitted_at":"2026-08-03T17:54:11Z","title":"UEmbed: Unified Sparse and Dense Multimodal Embeddings","version":1},"reference_index":58,"source":"arxiv_source","source_observed_at":"2026-08-04T04:19:08.249375Z"},"links":{"citing_paper":"/paper/2608.02583"},"observation_digest":"sha256:5fcfbf8a1094a92d2fbfd0369af53c50743f1acd743b2c5b7801a71e9af1f55d","observation_id":"7cb19990-fefa-477e-ac35-6730b4ec561c","resolution":{"observed_at":"2026-08-04T04:19:08.249375Z","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":"2026-08-04T04:19:08.382915Z","title":"Proceedings of the ACM SIGOPS 29th Symposium on Operating Systems Principles , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.02583","last_updated":"2026-08-03T17:54:11Z","snapshot_observed_at":"2026-08-12T13:33:06.916298Z","submitted_at":"2026-08-03T17:54:11Z","title":"UEmbed: Unified Sparse and Dense Multimodal Embeddings","version":1},"reference_index":59,"source":"arxiv_source","source_observed_at":"2026-08-04T04:19:08.382915Z"},"links":{"citing_paper":"/paper/2608.02583"},"observation_digest":"sha256:a83654f9057bc47856aae0d4eba13d2c51c84ac4541d124661b8499c0056e783","observation_id":"8d3b7478-14c4-483e-92f1-a6f5fbfbc7d8","resolution":{"observed_at":"2026-08-04T04:19:08.382915Z","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":"2026-08-04T04:19:08.575132Z","title":"Advances in neural information processing systems , volume=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.02583","last_updated":"2026-08-03T17:54:11Z","snapshot_observed_at":"2026-08-12T13:33:06.916298Z","submitted_at":"2026-08-03T17:54:11Z","title":"UEmbed: Unified Sparse and Dense Multimodal Embeddings","version":1},"reference_index":60,"source":"arxiv_source","source_observed_at":"2026-08-04T04:19:08.575132Z"},"links":{"citing_paper":"/paper/2608.02583"},"observation_digest":"sha256:5464e377deb0ce05fbbef134775e6dc5febccc9ad3d32a0e5e5d5cb9a331f7e6","observation_id":"675fe655-1299-4f9a-bf1b-5673c32194cd","resolution":{"observed_at":"2026-08-04T04:19:08.575132Z","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":"2026-08-04T04:19:08.709720Z","title":"NLTK : The Natural Language Toolkit","venue":null,"work_id":null,"year":2004},"citing_paper":{"arxiv_id":"2608.02583","last_updated":"2026-08-03T17:54:11Z","snapshot_observed_at":"2026-08-12T13:33:06.916298Z","submitted_at":"2026-08-03T17:54:11Z","title":"UEmbed: Unified Sparse and Dense Multimodal Embeddings","version":1},"reference_index":61,"source":"arxiv_source","source_observed_at":"2026-08-04T04:19:08.709720Z"},"links":{"citing_paper":"/paper/2608.02583"},"observation_digest":"sha256:3512b93c3428a597ddba80d51d4b4f91bb15996f0d9444d6d82dd45c8e4de62c","observation_id":"3383303b-79eb-4806-94ed-5dcbb2b0b596","resolution":{"observed_at":"2026-08-04T04:19:08.709720Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2004.05665","last_updated":"2020-04-12T18:09:02Z","snapshot_observed_at":"2026-08-09T03:07:30.511411Z","submitted_at":"2020-04-12T18:09:02Z","title":"Minimizing FLOPs to Learn Efficient Sparse Representations","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2004.05665","snapshot_observed_at":"2026-08-04T04:19:08.849928Z","title":"arXiv preprint arXiv:2004.05665 , year=","venue":null,"work_id":null,"year":2004},"citing_paper":{"arxiv_id":"2608.02583","last_updated":"2026-08-03T17:54:11Z","snapshot_observed_at":"2026-08-12T13:33:06.916298Z","submitted_at":"2026-08-03T17:54:11Z","title":"UEmbed: Unified Sparse and Dense Multimodal Embeddings","version":1},"reference_index":62,"source":"arxiv_source","source_observed_at":"2026-08-04T04:19:08.849928Z"},"links":{"cited_paper":"/paper/2004.05665","citing_paper":"/paper/2608.02583"},"observation_digest":"sha256:f92dc75d8dbf78420caac0e62a4fb240535d96dea92bfcd72b0f9883ed20224b","observation_id":"31aa7f4f-0a7e-4ab6-b4da-56a469f33518","resolution":{"observed_at":"2026-08-04T04:19:08.849928Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2602.21456","last_updated":"2026-06-19T07:08:02Z","snapshot_observed_at":"2026-08-17T02:20:02.632297Z","submitted_at":"2026-02-25T00:18:07Z","title":"Revisiting Text Ranking in Deep Research","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2602.21456","snapshot_observed_at":"2026-08-04T04:19:08.945996Z","title":"arXiv preprint arXiv:2602.21456 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.02583","last_updated":"2026-08-03T17:54:11Z","snapshot_observed_at":"2026-08-12T13:33:06.916298Z","submitted_at":"2026-08-03T17:54:11Z","title":"UEmbed: Unified Sparse and Dense Multimodal Embeddings","version":1},"reference_index":63,"source":"arxiv_source","source_observed_at":"2026-08-04T04:19:08.945996Z"},"links":{"cited_paper":"/paper/2602.21456","citing_paper":"/paper/2608.02583"},"observation_digest":"sha256:ebec55a4712b4b8ee1f5100542c29c886a94a847c1857f287dcf81015b31d019","observation_id":"26aaef36-ba78-4aed-b881-8a217a7ca1af","resolution":{"observed_at":"2026-08-04T04:19:08.945996Z","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":"2026-08-04T04:19:09.116591Z","title":"and Shen, Yelong and Wallis, Phillip and Allen-Zhu, Zeyuan and Li, Yuanzhi and Wang, Shean and Wang, Lu and Chen, Weizhu , booktitle=","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2608.02583","last_updated":"2026-08-03T17:54:11Z","snapshot_observed_at":"2026-08-12T13:33:06.916298Z","submitted_at":"2026-08-03T17:54:11Z","title":"UEmbed: Unified Sparse and Dense Multimodal Embeddings","version":1},"reference_index":64,"source":"arxiv_source","source_observed_at":"2026-08-04T04:19:09.116591Z"},"links":{"citing_paper":"/paper/2608.02583"},"observation_digest":"sha256:2df456eeeab483d53409501fa4ac63770be4131433348e97348069c0fe6e1885","observation_id":"a1400b41-a84e-4a3f-8477-7295257307b6","resolution":{"observed_at":"2026-08-04T04:19:09.116591Z","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":"2026-08-04T04:19:09.282754Z","title":"2025 , howpublished=","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2608.02583","last_updated":"2026-08-03T17:54:11Z","snapshot_observed_at":"2026-08-12T13:33:06.916298Z","submitted_at":"2026-08-03T17:54:11Z","title":"UEmbed: Unified Sparse and Dense Multimodal Embeddings","version":1},"reference_index":65,"source":"arxiv_source","source_observed_at":"2026-08-04T04:19:09.282754Z"},"links":{"citing_paper":"/paper/2608.02583"},"observation_digest":"sha256:e5a29ba793df34237d72971b79cb0beb9df3ad8336a6b0281f366695dcc83a7a","observation_id":"fb4e9daa-6d8c-40d5-b4cc-3240c6f6a674","resolution":{"observed_at":"2026-08-04T04:19:09.282754Z","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":"2026-08-04T04:19:09.392815Z","title":null,"venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2608.02583","last_updated":"2026-08-03T17:54:11Z","snapshot_observed_at":"2026-08-12T13:33:06.916298Z","submitted_at":"2026-08-03T17:54:11Z","title":"UEmbed: Unified Sparse and Dense Multimodal Embeddings","version":1},"reference_index":66,"source":"arxiv_source","source_observed_at":"2026-08-04T04:19:09.392815Z"},"links":{"citing_paper":"/paper/2608.02583"},"observation_digest":"sha256:bcd800de92a0e7f78ba4d0d8ef4573bd489f6dd265c240e40f85ad08eb179bf0","observation_id":"39d6e729-9906-4dab-92a7-eab7a4cd82bf","resolution":{"observed_at":"2026-08-04T04:19:09.392815Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2608.02583","last_updated":"2026-08-03T17:54:11Z","latest_version":1,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-12T13:33:06.916298Z","submitted_at":"2026-08-03T17:54:11Z","title":"UEmbed: Unified Sparse and Dense Multimodal Embeddings"},"reference_resolution":{"displayed":66,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":66,"verified_exact":0,"verified_fuzzy":0},"total_outbound_references":66},"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":"2026-08-19T06:32:44.657259+00:00","source":"crossref"},{"observed_at":"2026-08-19T06:32:39.956319+00:00","source":"retraction_watch"}],"thesis":"As of 19 August 2026, this Paper Citation Record lists 66 of 66 outbound references and 0 inbound Pith citation observations for arXiv:2608.02583."}