{"as_of":"2026-08-09T21:28:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:ceb879477fe5539d3186b612223ec5f7779139985c8e6c659d5508fa1a56ad2f","coverage":[{"denominator":0,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":14,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":14,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-09T06:31:02.800959+00:00","state":"measured"},{"denominator":14,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":14,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T05:57:22.724573Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":1,"source":"arxiv_reference","source_observed_at":"2026-08-05T02:28:24.338817Z","state":"measured"}],"external_citation_measurements":[{"count":10,"observed_at":"2026-08-05T02:28:24.338817Z","source":"arxiv_reference"}],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2102.09542","last_updated":"2021-02-18T18:44:50Z","snapshot_observed_at":"2026-08-05T10:02:06.651858Z","submitted_at":"2021-02-18T18:44:50Z","title":"SLAKE: A Semantically-Labeled Knowledge-Enhanced Dataset for Medical Visual Question Answering","version":1},"cited_work":{"arxiv_id":"2102.09542","doi":"10.48550/arxiv.2102.09542","metadata_source":"arxiv_reference","pith_arxiv_id":"2102.09542","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Slake: A semantically-labeled knowledge-enhanced dataset for medical visual question answering","venue":"arXiv (Cornell University)","work_id":"793780ed-4759-455b-80c3-13f1ad3ac7bd","year":2021},"citing_paper":{"arxiv_id":"2408.16213","last_updated":"2024-08-29T02:12:58Z","snapshot_observed_at":"2026-08-02T05:05:13.711617Z","submitted_at":"2024-08-29T02:12:58Z","title":"M4CXR: Exploring Multi-task Potentials of Multi-modal Large Language Models for Chest X-ray Interpretation","version":1},"reference_index":31,"source":"arxiv_source","source_observed_at":"2026-05-23T22:03:33.418989Z"},"links":{"cited_paper":"/paper/2102.09542","citing_paper":"/paper/2408.16213"},"observation_digest":"sha256:9f5a8882837afadb59b07c09e8df05b90c042ada9b1527698f1551064451e9f8","observation_id":"ff236a51-f776-4332-9aed-aa97066a4a28","resolution":{"observed_at":"2026-05-23T22:05:50.411712Z","resolver_source":"arxiv_id","status":"verified_exact"},"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":"2102.09542","last_updated":"2021-02-18T18:44:50Z","snapshot_observed_at":"2026-08-05T10:02:06.651858Z","submitted_at":"2021-02-18T18:44:50Z","title":"SLAKE: A Semantically-Labeled Knowledge-Enhanced Dataset for Medical Visual Question Answering","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2102.09542","snapshot_observed_at":"2026-08-07T05:57:22.724573Z","title":"Slake: A semantically- labeled knowledge-enhanced dataset for medical visual question answering","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2506.06600","last_updated":"2025-06-14T19:41:30Z","snapshot_observed_at":"2026-08-08T19:29:49.172087Z","submitted_at":"2025-06-07T00:26:23Z","title":"RARL: Improving Medical VLM Reasoning and Generalization with Reinforcement Learning and LoRA under Data and Hardware Constraints","version":2},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-07T05:57:22.724573Z"},"links":{"cited_paper":"/paper/2102.09542","citing_paper":"/paper/2506.06600"},"observation_digest":"sha256:ad4043e20e4964e24cc80ff0239200558f3679bd7ab976083cc208a2aca19561","observation_id":"0758ad61-c5fa-4d6f-b6c8-001ca2c3f319","resolution":{"observed_at":"2026-08-07T05:57:22.724573Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2102.09542","last_updated":"2021-02-18T18:44:50Z","snapshot_observed_at":"2026-08-05T10:02:06.651858Z","submitted_at":"2021-02-18T18:44:50Z","title":"SLAKE: A Semantically-Labeled Knowledge-Enhanced Dataset for Medical Visual Question Answering","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2102.09542","snapshot_observed_at":"2026-08-07T04:58:08.699216Z","title":"Slake: A semantically-labeled knowledge-enhanced dataset for medical visual question answering, 2021.https://arxiv.org/abs/2102.09542","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2506.09344","last_updated":"2025-06-11T02:50:49Z","snapshot_observed_at":"2026-08-08T17:53:50.843512Z","submitted_at":"2025-06-11T02:50:49Z","title":"Ming-Omni: A Unified Multimodal Model for Perception and Generation","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-07T04:58:08.699216Z"},"links":{"cited_paper":"/paper/2102.09542","citing_paper":"/paper/2506.09344"},"observation_digest":"sha256:4154f0c84a4ab8776b670c78c5546af6997433e97a32648c596106ac6094125b","observation_id":"241556af-9e91-45bc-b9e4-46a607fba19f","resolution":{"observed_at":"2026-08-07T04:58:08.699216Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2102.09542","last_updated":"2021-02-18T18:44:50Z","snapshot_observed_at":"2026-08-05T10:02:06.651858Z","submitted_at":"2021-02-18T18:44:50Z","title":"SLAKE: A Semantically-Labeled Knowledge-Enhanced Dataset for Medical Visual Question Answering","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2102.09542","snapshot_observed_at":"2026-08-07T00:23:28.726343Z","title":"Slake: A semantically- labeled knowledge-enhanced dataset for medical visual question answering, 2021","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2506.14451","last_updated":"2025-06-17T12:15:08Z","snapshot_observed_at":"2026-08-09T13:10:28.389400Z","submitted_at":"2025-06-17T12:15:08Z","title":"Adapting Lightweight Vision Language Models for Radiological Visual Question Answering","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-07T00:23:28.726343Z"},"links":{"cited_paper":"/paper/2102.09542","citing_paper":"/paper/2506.14451"},"observation_digest":"sha256:2784fcf751195456dc0616b8dede2110cb4a223f2ba0399359ff974f4292048b","observation_id":"30253ec1-9cae-49de-a3d9-70dd616e2b02","resolution":{"observed_at":"2026-08-07T00:23:28.726343Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2102.09542","last_updated":"2021-02-18T18:44:50Z","snapshot_observed_at":"2026-08-05T10:02:06.651858Z","submitted_at":"2021-02-18T18:44:50Z","title":"SLAKE: A Semantically-Labeled Knowledge-Enhanced Dataset for Medical Visual Question Answering","version":1},"cited_work":{"arxiv_id":"2102.09542","doi":"10.48550/arxiv.2102.09542","metadata_source":"arxiv_reference","pith_arxiv_id":"2102.09542","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Slake: A semantically-labeled knowledge-enhanced dataset for medical visual question answering","venue":"arXiv (Cornell University)","work_id":"793780ed-4759-455b-80c3-13f1ad3ac7bd","year":2021},"citing_paper":{"arxiv_id":"2605.05810","last_updated":"2026-05-07T07:46:17Z","snapshot_observed_at":"2026-07-06T23:18:22.301347Z","submitted_at":"2026-05-07T07:46:17Z","title":"CXR-ContraBench: Benchmarking Negated-Option Attraction in Medical VLMs","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-05-08T14:49:53.357083Z"},"links":{"cited_paper":"/paper/2102.09542","citing_paper":"/paper/2605.05810"},"observation_digest":"sha256:3e4724643b230a2736dff3be55d7ab91ba5c2c286912e8f18de8ae6adeb013f7","observation_id":"b3a5dcbc-b58a-4320-95ac-d0a41788426d","resolution":{"observed_at":"2026-05-11T18:41:09.615748Z","resolver_source":"arxiv_id","status":"verified_exact"},"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":"2102.09542","last_updated":"2021-02-18T18:44:50Z","snapshot_observed_at":"2026-08-05T10:02:06.651858Z","submitted_at":"2021-02-18T18:44:50Z","title":"SLAKE: A Semantically-Labeled Knowledge-Enhanced Dataset for Medical Visual Question Answering","version":1},"cited_work":{"arxiv_id":"2102.09542","doi":"10.48550/arxiv.2102.09542","metadata_source":"arxiv_reference","pith_arxiv_id":"2102.09542","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Slake: A semantically-labeled knowledge-enhanced dataset for medical visual question answering","venue":"arXiv (Cornell University)","work_id":"793780ed-4759-455b-80c3-13f1ad3ac7bd","year":2021},"citing_paper":{"arxiv_id":"2605.29163","last_updated":"2026-05-27T22:56:19Z","snapshot_observed_at":"2026-07-06T23:38:37.178378Z","submitted_at":"2026-05-27T22:56:19Z","title":"BCER Agent: Reliable Long-Horizon MRI Workflow Execution via Compilation, Artifact Binding, and Bounded Local Recovery","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-06-29T09:11:09.171906Z"},"links":{"cited_paper":"/paper/2102.09542","citing_paper":"/paper/2605.29163"},"observation_digest":"sha256:2d15f062d217aeeb3b8cc091ca65729eb83765cf02bc2fe7ed7bf2c1afb90d11","observation_id":"d2f8c311-7029-4d75-b37e-a5f6d95c7314","resolution":{"observed_at":"2026-06-29T09:13:15.611270Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"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":"2102.09542","last_updated":"2021-02-18T18:44:50Z","snapshot_observed_at":"2026-08-05T10:02:06.651858Z","submitted_at":"2021-02-18T18:44:50Z","title":"SLAKE: A Semantically-Labeled Knowledge-Enhanced Dataset for Medical Visual Question Answering","version":1},"cited_work":{"arxiv_id":"2102.09542","doi":"10.48550/arxiv.2102.09542","metadata_source":"arxiv_reference","pith_arxiv_id":"2102.09542","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Slake: A semantically-labeled knowledge-enhanced dataset for medical visual question answering","venue":"arXiv (Cornell University)","work_id":"793780ed-4759-455b-80c3-13f1ad3ac7bd","year":2021},"citing_paper":{"arxiv_id":"2606.01044","last_updated":"2026-05-31T06:25:53Z","snapshot_observed_at":"2026-08-01T08:55:54.438986Z","submitted_at":"2026-05-31T06:25:53Z","title":"Ask4VG: Risk-Aware Question Selection for Reducing Prior-Driven Answers in Medical VQA","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-06-28T17:21:52.460576Z"},"links":{"cited_paper":"/paper/2102.09542","citing_paper":"/paper/2606.01044"},"observation_digest":"sha256:cde2fe6bfd305ad649f90ed000a7583dd02ee4cafdf6b5ec00d74d6981746b9b","observation_id":"991549d6-23bb-4f31-b989-66593769ecd4","resolution":{"observed_at":"2026-06-28T17:22:24.354346Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"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":"2102.09542","last_updated":"2021-02-18T18:44:50Z","snapshot_observed_at":"2026-08-05T10:02:06.651858Z","submitted_at":"2021-02-18T18:44:50Z","title":"SLAKE: A Semantically-Labeled Knowledge-Enhanced Dataset for Medical Visual Question Answering","version":1},"cited_work":{"arxiv_id":"2102.09542","doi":"10.48550/arxiv.2102.09542","metadata_source":"arxiv_reference","pith_arxiv_id":"2102.09542","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Slake: A semantically-labeled knowledge-enhanced dataset for medical visual question answering","venue":"arXiv (Cornell University)","work_id":"793780ed-4759-455b-80c3-13f1ad3ac7bd","year":2021},"citing_paper":{"arxiv_id":"2606.03693","last_updated":"2026-06-02T14:14:27Z","snapshot_observed_at":"2026-07-06T23:43:55.632508Z","submitted_at":"2026-06-02T14:14:27Z","title":"Does Language Shift Break Medical Vision-Language Models? Indonesian Radiology Visual Question Answering Case Study","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-06-28T10:42:50.961855Z"},"links":{"cited_paper":"/paper/2102.09542","citing_paper":"/paper/2606.03693"},"observation_digest":"sha256:80194e2e99c5bfdce7d9ff967c35fa5e4edb71644d2181d2c2d30d6416264004","observation_id":"4f6aa956-24dd-47c5-8fcd-39bd044ae3cc","resolution":{"observed_at":"2026-07-02T02:46:28.061248Z","resolver_source":"arxiv_id","status":"verified_exact"},"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":"2102.09542","last_updated":"2021-02-18T18:44:50Z","snapshot_observed_at":"2026-08-05T10:02:06.651858Z","submitted_at":"2021-02-18T18:44:50Z","title":"SLAKE: A Semantically-Labeled Knowledge-Enhanced Dataset for Medical Visual Question Answering","version":1},"cited_work":{"arxiv_id":"2102.09542","doi":"10.48550/arxiv.2102.09542","metadata_source":"arxiv_reference","pith_arxiv_id":"2102.09542","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Slake: A semantically-labeled knowledge-enhanced dataset for medical visual question answering","venue":"arXiv (Cornell University)","work_id":"793780ed-4759-455b-80c3-13f1ad3ac7bd","year":2021},"citing_paper":{"arxiv_id":"2606.06696","last_updated":"2026-06-04T20:24:47Z","snapshot_observed_at":"2026-07-06T23:46:28.942186Z","submitted_at":"2026-06-04T20:24:47Z","title":"MMBU: A Massive Multi-modal Biomedical Understanding Benchmark to Probe the Perception Capabilities of Vision-Language Models","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-06-28T01:39:30.851276Z"},"links":{"cited_paper":"/paper/2102.09542","citing_paper":"/paper/2606.06696"},"observation_digest":"sha256:4f2d1e1fafb2dccf4750be4651ca00875459c39544e41d7e5cbd215cffb4bcba","observation_id":"16d241b0-53e1-44ad-bc4a-98a6a180e287","resolution":{"observed_at":"2026-07-02T12:56:57.624573Z","resolver_source":"arxiv_id","status":"verified_exact"},"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":"2102.09542","last_updated":"2021-02-18T18:44:50Z","snapshot_observed_at":"2026-08-05T10:02:06.651858Z","submitted_at":"2021-02-18T18:44:50Z","title":"SLAKE: A Semantically-Labeled Knowledge-Enhanced Dataset for Medical Visual Question Answering","version":1},"cited_work":{"arxiv_id":"2102.09542","doi":"10.48550/arxiv.2102.09542","metadata_source":"arxiv_reference","pith_arxiv_id":"2102.09542","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Slake: A semantically-labeled knowledge-enhanced dataset for medical visual question answering","venue":"arXiv (Cornell University)","work_id":"793780ed-4759-455b-80c3-13f1ad3ac7bd","year":2021},"citing_paper":{"arxiv_id":"2606.26458","last_updated":"2026-06-24T23:38:42Z","snapshot_observed_at":"2026-08-02T19:46:19.775072Z","submitted_at":"2026-06-24T23:38:42Z","title":"MKG-RAG-Bench: Benchmarking Retrieval in Multimodal Knowledge Graph-Augmented Generation","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-06-26T01:11:45.657964Z"},"links":{"cited_paper":"/paper/2102.09542","citing_paper":"/paper/2606.26458"},"observation_digest":"sha256:090664bef62f95320405b48c4181cc9367e69128b4a70b9e6f31b2327d4b7415","observation_id":"760d9c10-f816-4794-b725-c81b0e556114","resolution":{"observed_at":"2026-07-04T15:59:56.611990Z","resolver_source":"arxiv_id","status":"verified_exact"},"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":"2102.09542","last_updated":"2021-02-18T18:44:50Z","snapshot_observed_at":"2026-08-05T10:02:06.651858Z","submitted_at":"2021-02-18T18:44:50Z","title":"SLAKE: A Semantically-Labeled Knowledge-Enhanced Dataset for Medical Visual Question Answering","version":1},"cited_work":{"arxiv_id":"2102.09542","doi":"10.48550/arxiv.2102.09542","metadata_source":"arxiv_reference","pith_arxiv_id":"2102.09542","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Slake: A semantically-labeled knowledge-enhanced dataset for medical visual question answering","venue":"arXiv (Cornell University)","work_id":"793780ed-4759-455b-80c3-13f1ad3ac7bd","year":2021},"citing_paper":{"arxiv_id":"2606.28329","last_updated":"2026-05-19T15:18:23Z","snapshot_observed_at":"2026-07-07T00:02:29.000757Z","submitted_at":"2026-05-19T15:18:23Z","title":"$M^3 QuestionIng$: Multi-modal Multi-span Medical Question Answering","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-06-30T18:09:46.506953Z"},"links":{"cited_paper":"/paper/2102.09542","citing_paper":"/paper/2606.28329"},"observation_digest":"sha256:28994f91972ed5e2f320e48431aee3b1774a9c4c6d3a43ef95689cf494d437fd","observation_id":"c95c484d-6bb0-47e2-9dd0-1dea876d7f4e","resolution":{"observed_at":"2026-06-30T18:15:00.030039Z","resolver_source":"arxiv_id","status":"verified_exact"},"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":"2102.09542","last_updated":"2021-02-18T18:44:50Z","snapshot_observed_at":"2026-08-05T10:02:06.651858Z","submitted_at":"2021-02-18T18:44:50Z","title":"SLAKE: A Semantically-Labeled Knowledge-Enhanced Dataset for Medical Visual Question Answering","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2102.09542","snapshot_observed_at":"2026-07-13T05:07:42.040673Z","title":"SLAKE: A semantically-labeled knowledge-enhanced dataset for medical visual question answering","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2607.09142","last_updated":"2026-07-16T10:17:24Z","snapshot_observed_at":"2026-08-06T22:09:00.592774Z","submitted_at":"2026-07-10T06:52:05Z","title":"MedRealMM: A Real-World Multimodal Benchmark for Chinese Online Medical Consultation","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-07-13T05:07:42.040673Z"},"links":{"cited_paper":"/paper/2102.09542","citing_paper":"/paper/2607.09142"},"observation_digest":"sha256:6c2daed5d2a3521cae53b0e0761c89bb8945e3c4d54371654f404e965da7d220","observation_id":"5b899031-a318-42a9-9705-3bd2dca30042","resolution":{"observed_at":"2026-07-13T05:07:42.040673Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2102.09542","last_updated":"2021-02-18T18:44:50Z","snapshot_observed_at":"2026-08-05T10:02:06.651858Z","submitted_at":"2021-02-18T18:44:50Z","title":"SLAKE: A Semantically-Labeled Knowledge-Enhanced Dataset for Medical Visual Question Answering","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2102.09542","snapshot_observed_at":"2026-08-02T07:43:30.225146Z","title":"SLAKE: A semantically-labeled knowledge-enhanced dataset for medical visual question answering","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2607.09142","last_updated":"2026-07-16T10:17:24Z","snapshot_observed_at":"2026-08-06T22:09:00.592774Z","submitted_at":"2026-07-10T06:52:05Z","title":"MedRealMM: A Real-World Multimodal Benchmark for Chinese Online Medical Consultation","version":3},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-02T07:43:30.225146Z"},"links":{"cited_paper":"/paper/2102.09542","citing_paper":"/paper/2607.09142"},"observation_digest":"sha256:b1c7706e871b80249642d702bf8dbd25697213d7ba51d093397fb5fbd520597c","observation_id":"369af46b-79f9-4318-a36d-a07bcb501226","resolution":{"observed_at":"2026-08-02T07:43:30.225146Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2102.09542","last_updated":"2021-02-18T18:44:50Z","snapshot_observed_at":"2026-08-05T10:02:06.651858Z","submitted_at":"2021-02-18T18:44:50Z","title":"SLAKE: A Semantically-Labeled Knowledge-Enhanced Dataset for Medical Visual Question Answering","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2102.09542","snapshot_observed_at":"2026-08-01T05:38:57.686309Z","title":null,"venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2607.27564","last_updated":"2026-07-30T01:16:32Z","snapshot_observed_at":"2026-08-07T07:40:18.643570Z","submitted_at":"2026-07-30T01:16:32Z","title":"Inference-Time Agentic Decision Rules Beat Longer Evolving Search for Multi-Image Medical Reasoning","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-01T05:38:57.686309Z"},"links":{"cited_paper":"/paper/2102.09542","citing_paper":"/paper/2607.27564"},"observation_digest":"sha256:f1ac6d02fd66a0cb5ad406cc2b1011f2cd02790f593f14173cfa3f0f1ac667d8","observation_id":"e9d49227-2a8e-4a9e-a4cb-11ec7d912123","resolution":{"observed_at":"2026-08-01T05:38:57.686309Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2102.09542/citation-record","integrity":"/paper/2102.09542/integrity","json":"/paper/2102.09542/citation-record.json","paper":"/paper/2102.09542"},"outbound":[],"paper":{"arxiv_id":"2102.09542","last_updated":"2021-02-18T18:44:50Z","latest_version":1,"primary_category":"cs.CV","snapshot_observed_at":"2026-08-05T10:02:06.651858Z","submitted_at":"2021-02-18T18:44:50Z","title":"SLAKE: A Semantically-Labeled Knowledge-Enhanced Dataset for Medical Visual Question Answering"},"reference_resolution":{"displayed":0,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":0,"verified_exact":0,"verified_fuzzy":0},"total_outbound_references":0},"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 0 of 0 outbound references and 14 inbound Pith citation observations for arXiv:2102.09542."}