{"as_of":"2026-08-06T06:11:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:85c6456ab662461fd0e137ca883318c3089195fed85de65b24d56b028484d6b5","coverage":[{"denominator":63,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":63,"source":"paper_references, paper_reference_links","source_observed_at":"2026-05-17T20:29:39.744103Z","state":"measured"},{"denominator":67,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":67,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-05T06:32:48.257954+00:00","state":"measured"},{"denominator":4,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":4,"source":"paper_references, paper_reference_links","source_observed_at":"2026-07-14T06:30:16.612345Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"pith","source_observed_at":"2026-06-30T19:15:01.429618Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2511.17652","last_updated":"2026-04-06T19:52:36Z","snapshot_observed_at":"2026-08-01T03:53:15.171510Z","submitted_at":"2025-11-20T13:29:35Z","title":"TeamPath: Building MultiModal Pathology Experts with Reasoning AI Copilots","version":2},"cited_work":{"arxiv_id":"2511.17652","doi":null,"metadata_source":"pith","pith_arxiv_id":"2511.17652","snapshot_observed_at":"2026-06-30T19:15:01.429618Z","title":"TeamPath: Building MultiModal Pathology Experts with Reasoning AI Copilots","venue":"q-bio.QM","work_id":"0b05a313-749c-4451-8a24-dd1d49b05a3b","year":2025},"citing_paper":{"arxiv_id":"2605.06226","last_updated":"2026-05-09T22:50:37Z","snapshot_observed_at":"2026-07-06T23:18:41.400741Z","submitted_at":"2026-05-07T13:19:42Z","title":"A Versatile AI Agent for Rare Disease Diagnosis and Risk Gene Prioritization","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-05-08T10:10:41.877778Z"},"links":{"cited_paper":"/paper/2511.17652","citing_paper":"/paper/2605.06226"},"observation_digest":"sha256:5403b10fc4e6b299428071797bb110d0aac48ca95bb379a056db45b11f78e629","observation_id":"1a36df75-107e-4b58-8322-0fe6fb2dc80e","resolution":{"observed_at":"2026-05-11T20:11:09.252473Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2511.17652","last_updated":"2026-04-06T19:52:36Z","snapshot_observed_at":"2026-08-01T03:53:15.171510Z","submitted_at":"2025-11-20T13:29:35Z","title":"TeamPath: Building MultiModal Pathology Experts with Reasoning AI Copilots","version":2},"cited_work":{"arxiv_id":"2511.17652","doi":null,"metadata_source":"pith","pith_arxiv_id":"2511.17652","snapshot_observed_at":"2026-06-30T19:15:01.429618Z","title":"TeamPath: Building MultiModal Pathology Experts with Reasoning AI Copilots","venue":"q-bio.QM","work_id":"0b05a313-749c-4451-8a24-dd1d49b05a3b","year":2025},"citing_paper":{"arxiv_id":"2605.06226","last_updated":"2026-05-09T22:50:37Z","snapshot_observed_at":"2026-07-06T23:18:41.400741Z","submitted_at":"2026-05-07T13:19:42Z","title":"A Versatile AI Agent for Rare Disease Diagnosis and Risk Gene Prioritization","version":2},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-05-12T03:37:06.009960Z"},"links":{"cited_paper":"/paper/2511.17652","citing_paper":"/paper/2605.06226"},"observation_digest":"sha256:fae117945d8591600bead505eef28f33f4c0b47ac7e374afe8e4c0015643cae6","observation_id":"72561c4c-357d-43aa-84ee-3942b770e506","resolution":{"observed_at":"2026-05-12T07:11:27.034581Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2511.17652","last_updated":"2026-04-06T19:52:36Z","snapshot_observed_at":"2026-08-01T03:53:15.171510Z","submitted_at":"2025-11-20T13:29:35Z","title":"TeamPath: Building MultiModal Pathology Experts with Reasoning AI Copilots","version":2},"cited_work":{"arxiv_id":"2511.17652","doi":null,"metadata_source":"pith","pith_arxiv_id":"2511.17652","snapshot_observed_at":"2026-06-30T19:15:01.429618Z","title":"TeamPath: Building MultiModal Pathology Experts with Reasoning AI Copilots","venue":"q-bio.QM","work_id":"0b05a313-749c-4451-8a24-dd1d49b05a3b","year":2025},"citing_paper":{"arxiv_id":"2606.07549","last_updated":"2026-05-18T12:30:03Z","snapshot_observed_at":"2026-07-06T23:47:10.030985Z","submitted_at":"2026-05-18T12:30:03Z","title":"PathoSage: Towards Multi-Source Evidence Adjudication in Pathology via Experience-Aware Agentic Workflow","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-06-30T18:39:14.083052Z"},"links":{"cited_paper":"/paper/2511.17652","citing_paper":"/paper/2606.07549"},"observation_digest":"sha256:acf66126056c004522f1c824b8b854ca172f22970c5c560023fccfc60cea8196","observation_id":"b71ff2a9-ffb0-40a0-9afb-a8aceadf5d3c","resolution":{"observed_at":"2026-06-30T19:15:01.431179Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2511.17652","last_updated":"2026-04-06T19:52:36Z","snapshot_observed_at":"2026-08-01T03:53:15.171510Z","submitted_at":"2025-11-20T13:29:35Z","title":"TeamPath: Building MultiModal Pathology Experts with Reasoning AI Copilots","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2511.17652","snapshot_observed_at":"2026-07-14T06:30:16.612345Z","title":"Teampath: building multimodal pathology experts with reasoning ai copilots.arXiv preprint arXiv:2511.17652, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.11175","last_updated":"2026-07-13T07:16:50Z","snapshot_observed_at":"2026-07-16T23:19:14.481825Z","submitted_at":"2026-07-13T07:16:50Z","title":"The Path to Self-Evolving Clinical Systems: Scaling Medical Agents from Assistance to Autonomy","version":1},"reference_index":154,"source":"pdf_text","source_observed_at":"2026-07-14T06:30:16.612345Z"},"links":{"cited_paper":"/paper/2511.17652","citing_paper":"/paper/2607.11175"},"observation_digest":"sha256:db8d144511cf6d0e345d4bc4124f4ff22cc32903ee22dba10b844735ada51e66","observation_id":"17763079-ce69-4d23-bbe9-f94f340e4960","resolution":{"observed_at":"2026-07-14T06:30:16.612345Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2511.17652/citation-record","integrity":"/paper/2511.17652/integrity","json":"/paper/2511.17652/citation-record.json","paper":"/paper/2511.17652"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Artificial intelligence for digital and computational pathology","venue":null,"work_id":"71a67e14-32c1-475b-8638-f06546a1ed14","year":2023},"citing_paper":{"arxiv_id":"2511.17652","last_updated":"2026-04-06T19:52:36Z","snapshot_observed_at":"2026-08-01T03:53:15.171510Z","submitted_at":"2025-11-20T13:29:35Z","title":"TeamPath: Building MultiModal Pathology Experts with Reasoning AI Copilots","version":2},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-05-17T20:29:39.744103Z"},"links":{"citing_paper":"/paper/2511.17652"},"observation_digest":"sha256:eaa5c1f54940b74ab0fcc5582cfa0fd8d9d1e49dc3b4595dcfe59b66cfd63e04","observation_id":"753a5942-4c0b-42eb-9af5-bfc731c067e3","resolution":{"observed_at":"2026-05-17T20:30:11.868972Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Ar- tificialintelligenceindigitalpathology—newtoolsfordiagnosisandprecisiononcology.Nature reviews Clinical oncology, 16(11):703–715","venue":null,"work_id":"b1cf46ec-be11-4b47-ac3d-9d9824d0be1d","year":2019},"citing_paper":{"arxiv_id":"2511.17652","last_updated":"2026-04-06T19:52:36Z","snapshot_observed_at":"2026-08-01T03:53:15.171510Z","submitted_at":"2025-11-20T13:29:35Z","title":"TeamPath: Building MultiModal Pathology Experts with Reasoning AI Copilots","version":2},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-05-17T20:29:39.744103Z"},"links":{"citing_paper":"/paper/2511.17652"},"observation_digest":"sha256:4ac09f860f80ef133897a5739d69018c00ac0421920694add06525b88703e0c8","observation_id":"7463f22d-0df3-45db-be7b-03e83a713129","resolution":{"observed_at":"2026-05-17T20:30:11.871647Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Digital pathology and artificial intelligence.The lancet oncology, 20(5):e253–e261","venue":null,"work_id":"9841b125-2dee-4a74-8a55-ac9eb236308e","year":2019},"citing_paper":{"arxiv_id":"2511.17652","last_updated":"2026-04-06T19:52:36Z","snapshot_observed_at":"2026-08-01T03:53:15.171510Z","submitted_at":"2025-11-20T13:29:35Z","title":"TeamPath: Building MultiModal Pathology Experts with Reasoning AI Copilots","version":2},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-05-17T20:29:39.744103Z"},"links":{"citing_paper":"/paper/2511.17652"},"observation_digest":"sha256:9281442189e4bee122619c6cd8156f377d8efdfa3165f1f13ce1ac73374887e6","observation_id":"8489a1c9-2571-4593-98b4-a7b42a85a1d3","resolution":{"observed_at":"2026-05-17T20:30:11.856891Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Digital pathology: current status and future perspectives.Histopathology, 61(1):1–9","venue":null,"work_id":"de7a6eb4-5e26-4671-9596-bede2c33c8fe","year":2012},"citing_paper":{"arxiv_id":"2511.17652","last_updated":"2026-04-06T19:52:36Z","snapshot_observed_at":"2026-08-01T03:53:15.171510Z","submitted_at":"2025-11-20T13:29:35Z","title":"TeamPath: Building MultiModal Pathology Experts with Reasoning AI Copilots","version":2},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-05-17T20:29:39.744103Z"},"links":{"citing_paper":"/paper/2511.17652"},"observation_digest":"sha256:eff016bf3a204478d165916be4229e64bee61ddb3a2df6875d77e8909ff6fdf6","observation_id":"caa099d3-5e85-4a29-bf75-b47d53c99425","resolution":{"observed_at":"2026-05-17T20:30:11.854664Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Onthechallengesandperspectivesoffoundationmodels for medical image analysis.Medical image analysis, 91:102996","venue":null,"work_id":"f4dd06c5-84cf-4a61-ab68-0c2f7b036b03","year":2024},"citing_paper":{"arxiv_id":"2511.17652","last_updated":"2026-04-06T19:52:36Z","snapshot_observed_at":"2026-08-01T03:53:15.171510Z","submitted_at":"2025-11-20T13:29:35Z","title":"TeamPath: Building MultiModal Pathology Experts with Reasoning AI Copilots","version":2},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-05-17T20:29:39.744103Z"},"links":{"citing_paper":"/paper/2511.17652"},"observation_digest":"sha256:575460bcb562770c8f6019800688e4e118b0f6d9ba8fc6a252657e77cc5ba720","observation_id":"73315cbc-4e5b-402a-9ef7-df2c48273e30","resolution":{"observed_at":"2026-05-17T20:30:11.864412Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Towardsageneral- purpose foundation model for computational pathology.Nature Medicine, 30(3):850–862","venue":null,"work_id":"471b9e84-41b9-4427-ad42-c87828cfe1cb","year":2024},"citing_paper":{"arxiv_id":"2511.17652","last_updated":"2026-04-06T19:52:36Z","snapshot_observed_at":"2026-08-01T03:53:15.171510Z","submitted_at":"2025-11-20T13:29:35Z","title":"TeamPath: Building MultiModal Pathology Experts with Reasoning AI Copilots","version":2},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-05-17T20:29:39.744103Z"},"links":{"citing_paper":"/paper/2511.17652"},"observation_digest":"sha256:8d0f8fc5aab1bb8910f6bba28db448910bc02658b08b59d50bfed0553e796362","observation_id":"8a7440ba-6d41-40ea-8c1b-ca76e2f4a80f","resolution":{"observed_at":"2026-05-17T20:30:11.866699Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2307.12914","last_updated":"2023-07-25T17:56:38Z","snapshot_observed_at":"2026-08-02T21:29:30.878886Z","submitted_at":"2023-07-24T16:13:43Z","title":"Towards a Visual-Language Foundation Model for Computational Pathology","version":2},"cited_work":{"arxiv_id":"2307.12914","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2307.12914","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Towardsavisual-languagefoundation model for computational pathology","venue":null,"work_id":"8970dde2-78ee-4a52-986f-b14d544eefc9","year":2023},"citing_paper":{"arxiv_id":"2511.17652","last_updated":"2026-04-06T19:52:36Z","snapshot_observed_at":"2026-08-01T03:53:15.171510Z","submitted_at":"2025-11-20T13:29:35Z","title":"TeamPath: Building MultiModal Pathology Experts with Reasoning AI Copilots","version":2},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-05-17T20:29:39.744103Z"},"links":{"cited_paper":"/paper/2307.12914","citing_paper":"/paper/2511.17652"},"observation_digest":"sha256:7a2c7064f0d971c6c846b4962f05e665c10155d3227f48f36731171d34f2b193","observation_id":"8f3030c1-3dc8-425e-bf68-c72de011d744","resolution":{"observed_at":"2026-05-17T20:30:11.077024Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"A whole-slide foundation model for digital pathology from real-world data.Nature, pages 1–8","venue":null,"work_id":"74bc57b3-a154-43ea-843b-d65fbb29f4ce","year":2024},"citing_paper":{"arxiv_id":"2511.17652","last_updated":"2026-04-06T19:52:36Z","snapshot_observed_at":"2026-08-01T03:53:15.171510Z","submitted_at":"2025-11-20T13:29:35Z","title":"TeamPath: Building MultiModal Pathology Experts with Reasoning AI Copilots","version":2},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-05-17T20:29:39.744103Z"},"links":{"citing_paper":"/paper/2511.17652"},"observation_digest":"sha256:974a2b3a6f31699ce3598a17909b603a35de70fdfbc69eff21fba3408a337436","observation_id":"0c376b6c-2cb3-437f-8bf8-def077464e70","resolution":{"observed_at":"2026-05-17T20:30:11.852608Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Towards a generalizable pathology foundation model via unified knowledge distillation","venue":null,"work_id":"4f6766fa-3c51-4bf2-b468-4cd2444eb64e","year":2024},"citing_paper":{"arxiv_id":"2511.17652","last_updated":"2026-04-06T19:52:36Z","snapshot_observed_at":"2026-08-01T03:53:15.171510Z","submitted_at":"2025-11-20T13:29:35Z","title":"TeamPath: Building MultiModal Pathology Experts with Reasoning AI Copilots","version":2},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-05-17T20:29:39.744103Z"},"links":{"citing_paper":"/paper/2511.17652"},"observation_digest":"sha256:07dd79447a9642817ccf0c775b6d49415ce4855d20d3cd991511b6bf8368c406","observation_id":"ce974f18-9d7d-4e55-bcc3-6fbbc4da9b55","resolution":{"observed_at":"2026-05-17T20:30:11.861708Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Artificialintelligenceforprostatecancerdiagnostics.NatureCancer,Septem- ber 2025","venue":null,"work_id":"91942967-8648-44cc-b83c-06921250e857","year":2025},"citing_paper":{"arxiv_id":"2511.17652","last_updated":"2026-04-06T19:52:36Z","snapshot_observed_at":"2026-08-01T03:53:15.171510Z","submitted_at":"2025-11-20T13:29:35Z","title":"TeamPath: Building MultiModal Pathology Experts with Reasoning AI Copilots","version":2},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-05-17T20:29:39.744103Z"},"links":{"citing_paper":"/paper/2511.17652"},"observation_digest":"sha256:395b551111bbf09128ca8a4c6a396c08edc21c845e77f1d983c2047e9940296a","observation_id":"b41bd76b-b27c-4e4f-a012-91de56c9fad2","resolution":{"observed_at":"2026-05-17T20:30:11.859462Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Gen- erating dermatopathology reports from gigapixel whole slide images with histogpt.Nature Communications, 16(1):1–17","venue":null,"work_id":"3933eba5-1969-41d6-a9e3-d525c9729adb","year":2025},"citing_paper":{"arxiv_id":"2511.17652","last_updated":"2026-04-06T19:52:36Z","snapshot_observed_at":"2026-08-01T03:53:15.171510Z","submitted_at":"2025-11-20T13:29:35Z","title":"TeamPath: Building MultiModal Pathology Experts with Reasoning AI Copilots","version":2},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-05-17T20:29:39.744103Z"},"links":{"citing_paper":"/paper/2511.17652"},"observation_digest":"sha256:579e43b012f2dd11c939a579515b123ee84ecc57942549bfaf0cf7bda207a6ab","observation_id":"ab8387a8-41cf-48e8-8289-cf2c84533498","resolution":{"observed_at":"2026-05-17T20:30:11.835348Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"spemo: Exploring the capacity of foundation models for analyzing spatial multi-omic data.Nature Biomedical Engineering, pages 2025–01","venue":null,"work_id":"ac92a4ed-a403-4e2a-8f6a-3e9bc6576ffa","year":2025},"citing_paper":{"arxiv_id":"2511.17652","last_updated":"2026-04-06T19:52:36Z","snapshot_observed_at":"2026-08-01T03:53:15.171510Z","submitted_at":"2025-11-20T13:29:35Z","title":"TeamPath: Building MultiModal Pathology Experts with Reasoning AI Copilots","version":2},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-05-17T20:29:39.744103Z"},"links":{"citing_paper":"/paper/2511.17652"},"observation_digest":"sha256:3df1bdb7a7ac90a6578adb97be6cfeefe5e659041585961e60f8e12681adfd08","observation_id":"9837875c-5d26-464d-9dbf-01d3d4933a61","resolution":{"observed_at":"2026-05-17T20:30:11.805032Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2506.13063","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-30T19:15:01.466832Z","title":"Prism2: Unlocking multi-modal general pathology ai with clinical dialogue","venue":null,"work_id":"7766e20f-280d-48cd-92d6-2e53836bdd9e","year":2025},"citing_paper":{"arxiv_id":"2511.17652","last_updated":"2026-04-06T19:52:36Z","snapshot_observed_at":"2026-08-01T03:53:15.171510Z","submitted_at":"2025-11-20T13:29:35Z","title":"TeamPath: Building MultiModal Pathology Experts with Reasoning AI Copilots","version":2},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-05-17T20:29:39.744103Z"},"links":{"citing_paper":"/paper/2511.17652"},"observation_digest":"sha256:0bc1b81ab02e14d19f086dfb3ad585f3ebd79c546245624d8d1941a4f23b1a31","observation_id":"4bf65dd7-45b8-4e46-8cf0-806eb014f299","resolution":{"observed_at":"2026-05-17T20:30:11.152200Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T14:45:00.530903Z","title":"Vision-language models for vision tasks: A survey.IEEE transactions on pattern analysis and machine intelligence, 46(8):5625– 5644","venue":null,"work_id":"11471c3e-4db9-46da-8b72-5118bbe5bb71","year":2024},"citing_paper":{"arxiv_id":"2511.17652","last_updated":"2026-04-06T19:52:36Z","snapshot_observed_at":"2026-08-01T03:53:15.171510Z","submitted_at":"2025-11-20T13:29:35Z","title":"TeamPath: Building MultiModal Pathology Experts with Reasoning AI Copilots","version":2},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-05-17T20:29:39.744103Z"},"links":{"citing_paper":"/paper/2511.17652"},"observation_digest":"sha256:81fe50ebc35d428faca2d3c8b2a9cf1c4bd33f8a193c9350b5e933d351313c10","observation_id":"0fb3446a-510e-4542-9dfe-6a5f7551e5c0","resolution":{"observed_at":"2026-05-17T20:30:11.832637Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Slidechat: A large vision-language assistant for whole-slide pathology image understanding","venue":null,"work_id":"cf052d26-89b9-408c-bbd9-b72959eeb505","year":2025},"citing_paper":{"arxiv_id":"2511.17652","last_updated":"2026-04-06T19:52:36Z","snapshot_observed_at":"2026-08-01T03:53:15.171510Z","submitted_at":"2025-11-20T13:29:35Z","title":"TeamPath: Building MultiModal Pathology Experts with Reasoning AI Copilots","version":2},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-05-17T20:29:39.744103Z"},"links":{"citing_paper":"/paper/2511.17652"},"observation_digest":"sha256:a75379af1f20713806ee4bd817d8bdb4a2c38bf0cafd7941ea41bdecfa9d214c","observation_id":"6d0fe203-0f82-48f3-8094-ed96b394470b","resolution":{"observed_at":"2026-05-17T20:30:11.837992Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T03:44:29.524892Z","title":"A multimodal generative ai copilot for human pathology.Nature, 634(8033):466–473","venue":null,"work_id":"855eec21-4d8f-4565-9bf4-f23f596d6a29","year":2024},"citing_paper":{"arxiv_id":"2511.17652","last_updated":"2026-04-06T19:52:36Z","snapshot_observed_at":"2026-08-01T03:53:15.171510Z","submitted_at":"2025-11-20T13:29:35Z","title":"TeamPath: Building MultiModal Pathology Experts with Reasoning AI Copilots","version":2},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-05-17T20:29:39.744103Z"},"links":{"citing_paper":"/paper/2511.17652"},"observation_digest":"sha256:1a3f2416fbf605df52c4999df9775c8baac8ff4bfcecb85974b286e687ca67e4","observation_id":"70f06605-0cbb-40f2-b2b0-66f8cfb7f45f","resolution":{"observed_at":"2026-05-17T20:30:11.802957Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Avision–languagefoundationmodel for precision oncology.Nature, pages 1–10","venue":null,"work_id":"8fa1cb63-3a9c-4e5e-9955-693084ef94a1","year":2025},"citing_paper":{"arxiv_id":"2511.17652","last_updated":"2026-04-06T19:52:36Z","snapshot_observed_at":"2026-08-01T03:53:15.171510Z","submitted_at":"2025-11-20T13:29:35Z","title":"TeamPath: Building MultiModal Pathology Experts with Reasoning AI Copilots","version":2},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-05-17T20:29:39.744103Z"},"links":{"citing_paper":"/paper/2511.17652"},"observation_digest":"sha256:08d7cc2c86166ef578fb094f57dbe1b1196fd33619b8d04d6b2d1ac3c66547a8","observation_id":"6ccc0798-0280-4780-954c-8824f456f1eb","resolution":{"observed_at":"2026-05-17T20:30:11.795911Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"A visual–language foundation model for pathology image analysis using medical twitter.Nature medicine, 29(9):2307–2316","venue":null,"work_id":"99305200-35eb-438f-b1d6-192a2ab79818","year":2023},"citing_paper":{"arxiv_id":"2511.17652","last_updated":"2026-04-06T19:52:36Z","snapshot_observed_at":"2026-08-01T03:53:15.171510Z","submitted_at":"2025-11-20T13:29:35Z","title":"TeamPath: Building MultiModal Pathology Experts with Reasoning AI Copilots","version":2},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-05-17T20:29:39.744103Z"},"links":{"citing_paper":"/paper/2511.17652"},"observation_digest":"sha256:2c6eacf91ca76a3f8eccf87d63b2d745624925da7d94bcb656e99e8cad480dbc","observation_id":"9b7e45c2-7812-4f7a-9d39-e30806483702","resolution":{"observed_at":"2026-05-17T20:30:11.800884Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2501.17161","last_updated":"2025-05-26T17:16:45Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-01-28T18:59:44Z","title":"SFT Memorizes, RL Generalizes: A Comparative Study of Foundation Model Post-training","version":2},"cited_work":{"arxiv_id":"2501.17161","doi":"10.48550/arxiv.2501.17161","metadata_source":"pith","pith_arxiv_id":"2501.17161","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"SFT Memorizes, RL Generalizes: A Comparative Study of Foundation Model Post-training","venue":"cs.AI","work_id":"258dd934-025c-47f5-b4f6-5a0c1c338cc6","year":2025},"citing_paper":{"arxiv_id":"2511.17652","last_updated":"2026-04-06T19:52:36Z","snapshot_observed_at":"2026-08-01T03:53:15.171510Z","submitted_at":"2025-11-20T13:29:35Z","title":"TeamPath: Building MultiModal Pathology Experts with Reasoning AI Copilots","version":2},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-05-17T20:29:39.744103Z"},"links":{"cited_paper":"/paper/2501.17161","citing_paper":"/paper/2511.17652"},"observation_digest":"sha256:e08300a3467cdd0e955cda236637c84557bb0c356a0354cd0f3fa33175cf499e","observation_id":"5185a34b-9eb8-4d5a-b1fe-c77c76eea544","resolution":{"observed_at":"2026-05-17T20:30:11.092923Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-07-09T10:48:42.961784+00:00","source":"crossref_status_cache"},{"observed_at":"2026-07-09T10:48:42.961784+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2505.11404","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-10T18:57:31.588242Z","title":"arXiv preprint arXiv:2505.11404 , year=","venue":null,"work_id":"621e1d93-ff1f-4fd0-8a00-c884691b2bc1","year":2025},"citing_paper":{"arxiv_id":"2511.17652","last_updated":"2026-04-06T19:52:36Z","snapshot_observed_at":"2026-08-01T03:53:15.171510Z","submitted_at":"2025-11-20T13:29:35Z","title":"TeamPath: Building MultiModal Pathology Experts with Reasoning AI Copilots","version":2},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-05-17T20:29:39.744103Z"},"links":{"citing_paper":"/paper/2511.17652"},"observation_digest":"sha256:49addd4fa0a1234157115f2bfc8e2402011e179d9dc0c0dabc34af3bb476e7e1","observation_id":"29f59416-1dbc-4bc1-9a84-fbf0ff0cc56f","resolution":{"observed_at":"2026-05-17T20:30:11.148282Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2505.15687","last_updated":"2025-05-21T16:03:03Z","snapshot_observed_at":"2026-08-04T18:55:27.555086Z","submitted_at":"2025-05-21T16:03:03Z","title":"Discovering Pathology Rationale and Token Allocation for Efficient Multimodal Pathology Reasoning","version":1},"cited_work":{"arxiv_id":"2505.15687","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2505.15687","snapshot_observed_at":"2026-07-02T21:47:27.810427Z","title":"Discovering pathology rationale and tokenallocationforefficientmultimodalpathologyreasoning.arXivpreprint","venue":null,"work_id":"2a1fc5a8-6708-40dc-a45d-c770ba515622","year":2025},"citing_paper":{"arxiv_id":"2511.17652","last_updated":"2026-04-06T19:52:36Z","snapshot_observed_at":"2026-08-01T03:53:15.171510Z","submitted_at":"2025-11-20T13:29:35Z","title":"TeamPath: Building MultiModal Pathology Experts with Reasoning AI Copilots","version":2},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-05-17T20:29:39.744103Z"},"links":{"cited_paper":"/paper/2505.15687","citing_paper":"/paper/2511.17652"},"observation_digest":"sha256:12d6adfd591d02f9ff311a87f67ef44dc5b2566c1fa6535fdbb9eea5332f3086","observation_id":"a98639b0-4254-4aa2-b357-e09a7d157242","resolution":{"observed_at":"2026-05-17T20:30:11.129835Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2504.09258","last_updated":"2025-04-18T07:21:19Z","snapshot_observed_at":"2026-07-06T21:08:23.695370Z","submitted_at":"2025-04-12T15:32:16Z","title":"PathVLM-R1: A Reinforcement Learning-Driven Reasoning Model for Pathology Visual-Language Tasks","version":2},"cited_work":{"arxiv_id":"2504.09258","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2504.09258","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"arXiv preprint arXiv:2504.09258 , year=","venue":null,"work_id":"e76c1e44-fb58-46b1-9d6f-66f80e4a9d33","year":2025},"citing_paper":{"arxiv_id":"2511.17652","last_updated":"2026-04-06T19:52:36Z","snapshot_observed_at":"2026-08-01T03:53:15.171510Z","submitted_at":"2025-11-20T13:29:35Z","title":"TeamPath: Building MultiModal Pathology Experts with Reasoning AI Copilots","version":2},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-05-17T20:29:39.744103Z"},"links":{"cited_paper":"/paper/2504.09258","citing_paper":"/paper/2511.17652"},"observation_digest":"sha256:930e7fbd8bb16b8fc95f648046b6e7e26962286ef0d07cca2bba15bda287502c","observation_id":"24d284b3-9eda-4a8e-88fe-ff1b26524c83","resolution":{"observed_at":"2026-05-17T20:30:11.111658Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Pathgen-1.6 m: 1.6 million pathology image-text pairs generation through multi-agent collaboration","venue":null,"work_id":"dd15af26-52b1-4f4b-89e2-fa84b35942ff","year":null},"citing_paper":{"arxiv_id":"2511.17652","last_updated":"2026-04-06T19:52:36Z","snapshot_observed_at":"2026-08-01T03:53:15.171510Z","submitted_at":"2025-11-20T13:29:35Z","title":"TeamPath: Building MultiModal Pathology Experts with Reasoning AI Copilots","version":2},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-05-17T20:29:39.744103Z"},"links":{"citing_paper":"/paper/2511.17652"},"observation_digest":"sha256:673de890f5fb78c704fd4ba48d788125c2252d089d9112d353fac6190a15e68f","observation_id":"91598d2a-f912-4ee6-b1b4-cb08d62394c2","resolution":{"observed_at":"2026-05-17T20:30:11.798531Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"The cancer genome atlas pan- cancer analysis project.Nature genetics, 45(10):1113–1120","venue":null,"work_id":"f50b531e-2d1b-4ccd-9f4e-54fe886dabaa","year":2013},"citing_paper":{"arxiv_id":"2511.17652","last_updated":"2026-04-06T19:52:36Z","snapshot_observed_at":"2026-08-01T03:53:15.171510Z","submitted_at":"2025-11-20T13:29:35Z","title":"TeamPath: Building MultiModal Pathology Experts with Reasoning AI Copilots","version":2},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-05-17T20:29:39.744103Z"},"links":{"citing_paper":"/paper/2511.17652"},"observation_digest":"sha256:5d23a9e89026b182f413c22037d90c32097eb069dcb5912bd5fb283094ed365d","observation_id":"d864f836-00a8-46b0-a7db-3463f7695578","resolution":{"observed_at":"2026-05-17T20:30:11.777495Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Openai o3 and o4-mini system card","venue":null,"work_id":"7879f57e-a7d2-4117-8451-91e7f89312d1","year":2025},"citing_paper":{"arxiv_id":"2511.17652","last_updated":"2026-04-06T19:52:36Z","snapshot_observed_at":"2026-08-01T03:53:15.171510Z","submitted_at":"2025-11-20T13:29:35Z","title":"TeamPath: Building MultiModal Pathology Experts with Reasoning AI Copilots","version":2},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-05-17T20:29:39.744103Z"},"links":{"citing_paper":"/paper/2511.17652"},"observation_digest":"sha256:c6fb6e0b69bfd6576ff84b014a25e1b907faf91c535cd06daf40f9cf79e1b725","observation_id":"4bc0897f-9d0b-4047-9e21-ca73e88fe51b","resolution":{"observed_at":"2026-05-17T20:30:11.789144Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2003.10286","last_updated":"2020-03-07T17:55:41Z","snapshot_observed_at":"2026-07-06T09:06:42.071993Z","submitted_at":"2020-03-07T17:55:41Z","title":"PathVQA: 30000+ Questions for Medical Visual Question Answering","version":1},"cited_work":{"arxiv_id":"2003.10286","doi":null,"metadata_source":"pith","pith_arxiv_id":"2003.10286","snapshot_observed_at":"2026-07-10T18:57:31.568292Z","title":"PathVQA: 30000+ Questions for Medical Visual Question Answering","venue":"cs.CL","work_id":"4e35c15f-5a72-4a89-a773-9d4036871506","year":2020},"citing_paper":{"arxiv_id":"2511.17652","last_updated":"2026-04-06T19:52:36Z","snapshot_observed_at":"2026-08-01T03:53:15.171510Z","submitted_at":"2025-11-20T13:29:35Z","title":"TeamPath: Building MultiModal Pathology Experts with Reasoning AI Copilots","version":2},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-05-17T20:29:39.744103Z"},"links":{"cited_paper":"/paper/2003.10286","citing_paper":"/paper/2511.17652"},"observation_digest":"sha256:84f3bdb4e6a909c6a68fa4059e02edcacf7615a6a20b5fdba5f2cc2cb6636850","observation_id":"52e4ec45-9ddc-4de4-8fbf-883ca87aec3b","resolution":{"observed_at":"2026-05-17T20:30:11.143351Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Pathmmu: A massive multimodal expert-level benchmarkforunderstandingandreasoninginpathology","venue":null,"work_id":"b1f2ccd9-6126-4f07-8b78-5fcdcebf1577","year":2024},"citing_paper":{"arxiv_id":"2511.17652","last_updated":"2026-04-06T19:52:36Z","snapshot_observed_at":"2026-08-01T03:53:15.171510Z","submitted_at":"2025-11-20T13:29:35Z","title":"TeamPath: Building MultiModal Pathology Experts with Reasoning AI Copilots","version":2},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-05-17T20:29:39.744103Z"},"links":{"citing_paper":"/paper/2511.17652"},"observation_digest":"sha256:172cc08216edeab01328afb3ddabcff6074b1ac1e9037c77d821c513ff4fa318","observation_id":"8f7cbc95-4a45-484e-8ccf-dca61b765dd3","resolution":{"observed_at":"2026-05-17T20:30:11.756095Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Song, Ming Y","venue":null,"work_id":"d7095b5d-feec-48ec-9c3c-d70902c8a9d4","year":2024},"citing_paper":{"arxiv_id":"2511.17652","last_updated":"2026-04-06T19:52:36Z","snapshot_observed_at":"2026-08-01T03:53:15.171510Z","submitted_at":"2025-11-20T13:29:35Z","title":"TeamPath: Building MultiModal Pathology Experts with Reasoning AI Copilots","version":2},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-05-17T20:29:39.744103Z"},"links":{"citing_paper":"/paper/2511.17652"},"observation_digest":"sha256:115d2da86d4faae7518e293f68c08672cb8efc5eb3f7bdca94773eb805b95ffe","observation_id":"f4985ea8-73c7-48b6-927b-8292f75810d0","resolution":{"observed_at":"2026-05-17T20:30:11.840235Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Stimage- 1k4m: A histopathology image-gene expression dataset for spatial transcriptomics.Advances in Neural Information Processing Systems, 37:35796–35823","venue":null,"work_id":"cbe5b0df-de83-4def-bc63-de54fe0e6846","year":2024},"citing_paper":{"arxiv_id":"2511.17652","last_updated":"2026-04-06T19:52:36Z","snapshot_observed_at":"2026-08-01T03:53:15.171510Z","submitted_at":"2025-11-20T13:29:35Z","title":"TeamPath: Building MultiModal Pathology Experts with Reasoning AI Copilots","version":2},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-05-17T20:29:39.744103Z"},"links":{"citing_paper":"/paper/2511.17652"},"observation_digest":"sha256:15e24a7d0b7b439e0a4246814868b6b97baab4255152ec72a8d909dc5a3aa3b2","observation_id":"73818fb2-2b98-4b34-9e97-a5fda022c239","resolution":{"observed_at":"2026-05-17T20:30:11.775046Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2501.12948","last_updated":"2026-01-04T03:57:36Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-01-22T15:19:35Z","title":"DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning","version":2},"cited_work":{"arxiv_id":"2501.12948","doi":"10.1016/j.artmed.2024.103001","metadata_source":"pith","pith_arxiv_id":"2501.12948","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning","venue":"cs.CL","work_id":"e6b75ad5-2877-4168-97c8-710407094d20","year":2025},"citing_paper":{"arxiv_id":"2511.17652","last_updated":"2026-04-06T19:52:36Z","snapshot_observed_at":"2026-08-01T03:53:15.171510Z","submitted_at":"2025-11-20T13:29:35Z","title":"TeamPath: Building MultiModal Pathology Experts with Reasoning AI Copilots","version":2},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-05-17T20:29:39.744103Z"},"links":{"cited_paper":"/paper/2501.12948","citing_paper":"/paper/2511.17652"},"observation_digest":"sha256:6551a8771e97b2cfc812cb1a3d46d2d8b68f56e662d157605733f0b0e2206bb9","observation_id":"60f3f7de-7eb1-4943-8141-9ba937d53b36","resolution":{"observed_at":"2026-05-17T20:30:11.164073Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2010.12435","last_updated":"2020-10-06T00:36:55Z","snapshot_observed_at":"2026-08-02T06:31:20.270994Z","submitted_at":"2020-10-06T00:36:55Z","title":"Pathological Visual Question Answering","version":1},"cited_work":{"arxiv_id":"2010.12435","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2010.12435","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Pathological visual question answering","venue":null,"work_id":"78c40a09-1e0a-44c1-a3d6-c84b52a7554c","year":2010},"citing_paper":{"arxiv_id":"2511.17652","last_updated":"2026-04-06T19:52:36Z","snapshot_observed_at":"2026-08-01T03:53:15.171510Z","submitted_at":"2025-11-20T13:29:35Z","title":"TeamPath: Building MultiModal Pathology Experts with Reasoning AI Copilots","version":2},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-05-17T20:29:39.744103Z"},"links":{"cited_paper":"/paper/2010.12435","citing_paper":"/paper/2511.17652"},"observation_digest":"sha256:aa23a780342c18245f850283134c03b635b46a5d40420905c5f8be9601278a2d","observation_id":"8605bc63-2d64-4d2d-b85f-3a98561862ce","resolution":{"observed_at":"2026-05-17T20:30:11.168782Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2407.10671","last_updated":"2024-09-10T13:25:53Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-07-15T12:35:42Z","title":"Qwen2 Technical Report","version":4},"cited_work":{"arxiv_id":"2407.10671","doi":"10.18653/v1/2024.naacl-long.246","metadata_source":"pith","pith_arxiv_id":"2407.10671","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Qwen2 Technical Report","venue":"cs.CL","work_id":"a1857881-ab9b-4b80-9b5f-9ae4b5c2566d","year":2024},"citing_paper":{"arxiv_id":"2511.17652","last_updated":"2026-04-06T19:52:36Z","snapshot_observed_at":"2026-08-01T03:53:15.171510Z","submitted_at":"2025-11-20T13:29:35Z","title":"TeamPath: Building MultiModal Pathology Experts with Reasoning AI Copilots","version":2},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-05-17T20:29:39.744103Z"},"links":{"cited_paper":"/paper/2407.10671","citing_paper":"/paper/2511.17652"},"observation_digest":"sha256:bee76ca39688f597c49d34ebc6bef582ff27a278161f0ff8328a4279802d9bd1","observation_id":"3c6d2913-7a9e-4521-9e21-4575b6d84a51","resolution":{"observed_at":"2026-05-17T20:30:11.097658Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2504.10479","last_updated":"2025-04-19T03:47:21Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-04-14T17:59:25Z","title":"InternVL3: Exploring Advanced Training and Test-Time Recipes for Open-Source Multimodal Models","version":3},"cited_work":{"arxiv_id":"2504.10479","doi":"10.48550/arxiv.2504.10479","metadata_source":"pith","pith_arxiv_id":"2504.10479","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"InternVL3: Exploring Advanced Training and Test-Time Recipes for Open-Source Multimodal Models","venue":"cs.CV","work_id":"fe8637aa-12bc-4434-8d36-9f57b5eebcbe","year":2025},"citing_paper":{"arxiv_id":"2511.17652","last_updated":"2026-04-06T19:52:36Z","snapshot_observed_at":"2026-08-01T03:53:15.171510Z","submitted_at":"2025-11-20T13:29:35Z","title":"TeamPath: Building MultiModal Pathology Experts with Reasoning AI Copilots","version":2},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-05-17T20:29:39.744103Z"},"links":{"cited_paper":"/paper/2504.10479","citing_paper":"/paper/2511.17652"},"observation_digest":"sha256:2e8d7f127ed21bcb2c97d932df675c5d116eaceba82ea7e527fec56cd699ece7","observation_id":"50f40bc7-ff7a-4133-b8af-763bb33c9c00","resolution":{"observed_at":"2026-05-17T20:30:11.103194Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-05-20T07:54:09.017512+00:00","source":"crossref_status_cache"},{"observed_at":"2026-05-20T07:54:09.017512+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2507.05201","last_updated":"2026-04-06T19:50:20Z","snapshot_observed_at":"2026-08-02T22:39:49.756195Z","submitted_at":"2025-07-07T17:01:44Z","title":"MedGemma Technical Report","version":4},"cited_work":{"arxiv_id":"2507.05201","doi":"10.48550/arxiv.2507.05201","metadata_source":"pith","pith_arxiv_id":"2507.05201","snapshot_observed_at":"2026-08-05T02:49:54.815029Z","title":"MedGemma Technical Report","venue":"cs.AI","work_id":"3d3f25c0-31e8-4859-bb3d-0d719b47a63d","year":2025},"citing_paper":{"arxiv_id":"2511.17652","last_updated":"2026-04-06T19:52:36Z","snapshot_observed_at":"2026-08-01T03:53:15.171510Z","submitted_at":"2025-11-20T13:29:35Z","title":"TeamPath: Building MultiModal Pathology Experts with Reasoning AI Copilots","version":2},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-05-17T20:29:39.744103Z"},"links":{"cited_paper":"/paper/2507.05201","citing_paper":"/paper/2511.17652"},"observation_digest":"sha256:515cdd2e992594e43721be36ecb0e0ed83f702778138354ec6da059b367471f2","observation_id":"946072c0-400a-48d9-b0b3-18f68fc46abb","resolution":{"observed_at":"2026-05-17T20:30:11.086661Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2508.02669","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-04T12:49:52.205129Z","title":"arXiv preprint arXiv:2508.02669 , year=","venue":null,"work_id":"0dafa899-2698-4eb8-8bfb-00d88f7dd52c","year":2025},"citing_paper":{"arxiv_id":"2511.17652","last_updated":"2026-04-06T19:52:36Z","snapshot_observed_at":"2026-08-01T03:53:15.171510Z","submitted_at":"2025-11-20T13:29:35Z","title":"TeamPath: Building MultiModal Pathology Experts with Reasoning AI Copilots","version":2},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-05-17T20:29:39.744103Z"},"links":{"citing_paper":"/paper/2511.17652"},"observation_digest":"sha256:ea71297f1f63238281f5d358957689618c40317291d2ad211510445d4d608422","observation_id":"4e78b69d-9781-4e46-88b6-8549f8d92e5d","resolution":{"observed_at":"2026-05-17T20:30:11.081611Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Lipoblast: morphologic features and diagnostic value.Journal of UOEH, 36(2):115–121","venue":null,"work_id":"66a7c3fa-cc84-4345-b81d-3bd56e774ee5","year":2014},"citing_paper":{"arxiv_id":"2511.17652","last_updated":"2026-04-06T19:52:36Z","snapshot_observed_at":"2026-08-01T03:53:15.171510Z","submitted_at":"2025-11-20T13:29:35Z","title":"TeamPath: Building MultiModal Pathology Experts with Reasoning AI Copilots","version":2},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-05-17T20:29:39.744103Z"},"links":{"citing_paper":"/paper/2511.17652"},"observation_digest":"sha256:57ef8c5d9a916fb19444f3f88990f8ebce6dcf3fc5317ff905e3687a0ecdcb4f","observation_id":"0d1c1b32-b354-47f4-88e1-680f90ab88bc","resolution":{"observed_at":"2026-05-17T20:30:11.753816Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-10T02:06:42.560527Z","title":"Gaia: a benchmark for general ai assistants","venue":null,"work_id":"a7341f04-163e-406f-81d5-6ddb1dfd000f","year":2023},"citing_paper":{"arxiv_id":"2511.17652","last_updated":"2026-04-06T19:52:36Z","snapshot_observed_at":"2026-08-01T03:53:15.171510Z","submitted_at":"2025-11-20T13:29:35Z","title":"TeamPath: Building MultiModal Pathology Experts with Reasoning AI Copilots","version":2},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-05-17T20:29:39.744103Z"},"links":{"citing_paper":"/paper/2511.17652"},"observation_digest":"sha256:1c358c157d1fa4c0e3f3999790a02e288782b039c4aeefe04e2c48cfb4523176","observation_id":"34bda4ac-f232-4cd0-a6b4-67a4e1b51537","resolution":{"observed_at":"2026-05-17T20:30:11.758434Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2505.04638","last_updated":"2026-04-06T18:12:55Z","snapshot_observed_at":"2026-08-01T16:43:54.783975Z","submitted_at":"2025-05-03T14:21:48Z","title":"Advancing AI Research Assistants with Expert-Involved Learning","version":5},"cited_work":{"arxiv_id":"2505.04638","doi":null,"metadata_source":"pith","pith_arxiv_id":"2505.04638","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Advancing AI Research Assistants with Expert-Involved Learning","venue":"cs.AI","work_id":"3f0bc7ca-4bf5-471d-b311-0ceb36ab054e","year":2025},"citing_paper":{"arxiv_id":"2511.17652","last_updated":"2026-04-06T19:52:36Z","snapshot_observed_at":"2026-08-01T03:53:15.171510Z","submitted_at":"2025-11-20T13:29:35Z","title":"TeamPath: Building MultiModal Pathology Experts with Reasoning AI Copilots","version":2},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-05-17T20:29:39.744103Z"},"links":{"cited_paper":"/paper/2505.04638","citing_paper":"/paper/2511.17652"},"observation_digest":"sha256:580b9e4440e59f33c53fc394feaf86b4588278a03659cbf6652f3a8ed218e981","observation_id":"6ecd1356-5dff-4f38-9cc9-9c60da0d15ff","resolution":{"observed_at":"2026-05-17T20:30:11.120460Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2408.03314","last_updated":"2024-08-06T17:35:05Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-08-06T17:35:05Z","title":"Scaling LLM Test-Time Compute Optimally can be More Effective than Scaling Model Parameters","version":1},"cited_work":{"arxiv_id":"2408.03314","doi":"10.18653/v1/2025.acl-long.1486","metadata_source":"pith","pith_arxiv_id":"2408.03314","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"Scaling LLM Test-Time Compute Optimally can be More Effective than Scaling Model Parameters","venue":"cs.LG","work_id":"a8d50b24-bdf5-46ed-bc4f-2927dfd81f1d","year":2024},"citing_paper":{"arxiv_id":"2511.17652","last_updated":"2026-04-06T19:52:36Z","snapshot_observed_at":"2026-08-01T03:53:15.171510Z","submitted_at":"2025-11-20T13:29:35Z","title":"TeamPath: Building MultiModal Pathology Experts with Reasoning AI Copilots","version":2},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-05-17T20:29:39.744103Z"},"links":{"cited_paper":"/paper/2408.03314","citing_paper":"/paper/2511.17652"},"observation_digest":"sha256:af271251cfec4ea78909a50135fe453fb20c316e0aa5a3330857bc49237e6fce","observation_id":"a2f1c4c2-2677-41c8-84ca-0106ce44070a","resolution":{"observed_at":"2026-05-17T20:30:11.139647Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-10T07:26:54.787661Z","title":"Gpt-4 technical report","venue":null,"work_id":"388f534c-855a-4366-b933-f07bf3e2db5f","year":2023},"citing_paper":{"arxiv_id":"2511.17652","last_updated":"2026-04-06T19:52:36Z","snapshot_observed_at":"2026-08-01T03:53:15.171510Z","submitted_at":"2025-11-20T13:29:35Z","title":"TeamPath: Building MultiModal Pathology Experts with Reasoning AI Copilots","version":2},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-05-17T20:29:39.744103Z"},"links":{"citing_paper":"/paper/2511.17652"},"observation_digest":"sha256:f6a4b209e07fefea9852979e9c454f7ede05a44b53338b202a839386238f869f","observation_id":"eb384ef3-89e7-414b-b52e-c70e2c7438b5","resolution":{"observed_at":"2026-05-17T20:30:11.850150Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-10T10:37:02.032120Z","title":"Bleu: a method for automatic evaluation of machine translation","venue":null,"work_id":"3767906b-1763-489b-9cad-ef5ce131c855","year":2002},"citing_paper":{"arxiv_id":"2511.17652","last_updated":"2026-04-06T19:52:36Z","snapshot_observed_at":"2026-08-01T03:53:15.171510Z","submitted_at":"2025-11-20T13:29:35Z","title":"TeamPath: Building MultiModal Pathology Experts with Reasoning AI Copilots","version":2},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-05-17T20:29:39.744103Z"},"links":{"citing_paper":"/paper/2511.17652"},"observation_digest":"sha256:3864fc6c9da3e5f9b08ac4a7c2e6bd27bdd0bda8dfed18429fc5226fda7e9c6d","observation_id":"1af039bb-f3f3-4817-9246-d517a0213682","resolution":{"observed_at":"2026-05-17T20:30:11.829616Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Rouge: A package for automatic evaluation of summaries","venue":null,"work_id":"dfb331d5-83bf-4b8b-bb79-bbbb785ac760","year":2004},"citing_paper":{"arxiv_id":"2511.17652","last_updated":"2026-04-06T19:52:36Z","snapshot_observed_at":"2026-08-01T03:53:15.171510Z","submitted_at":"2025-11-20T13:29:35Z","title":"TeamPath: Building MultiModal Pathology Experts with Reasoning AI Copilots","version":2},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-05-17T20:29:39.744103Z"},"links":{"citing_paper":"/paper/2511.17652"},"observation_digest":"sha256:77ad708d4a7376d7f9274321a4b22a07638b6ea76e62e92e3f472d0a8c9dd821","observation_id":"e9699dc1-66a4-4261-b0f3-927f3ed1a681","resolution":{"observed_at":"2026-05-17T20:30:11.843166Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Bertscore: Eval- uating text generation with bert","venue":null,"work_id":"9d3d6938-cf23-461d-9d9a-70e80907efe8","year":null},"citing_paper":{"arxiv_id":"2511.17652","last_updated":"2026-04-06T19:52:36Z","snapshot_observed_at":"2026-08-01T03:53:15.171510Z","submitted_at":"2025-11-20T13:29:35Z","title":"TeamPath: Building MultiModal Pathology Experts with Reasoning AI Copilots","version":2},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-05-17T20:29:39.744103Z"},"links":{"citing_paper":"/paper/2511.17652"},"observation_digest":"sha256:9cafae49cc9d96a8cfada8663ae94ed807d0599b7cacd2194ae1c466451339e6","observation_id":"ba79d40c-f46c-416c-b4d0-0c948883feab","resolution":{"observed_at":"2026-05-17T20:30:11.847949Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Quickumls: a fast, unsupervised approach for medical concept extraction","venue":null,"work_id":"4e52d1e4-8f3a-4710-a681-0862a1a0fa95","year":2016},"citing_paper":{"arxiv_id":"2511.17652","last_updated":"2026-04-06T19:52:36Z","snapshot_observed_at":"2026-08-01T03:53:15.171510Z","submitted_at":"2025-11-20T13:29:35Z","title":"TeamPath: Building MultiModal Pathology Experts with Reasoning AI Copilots","version":2},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-05-17T20:29:39.744103Z"},"links":{"citing_paper":"/paper/2511.17652"},"observation_digest":"sha256:f15b4c691e9ed960762c0c029b5c9169754cca8a94f0f800216ce6d5c635417c","observation_id":"1756de05-b96a-41f4-9736-fb9974cf3e04","resolution":{"observed_at":"2026-05-17T20:30:11.793271Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"A visual–omics foundation model to bridge histopathology with spatial transcriptomics.Nature Methods, pages 1–15","venue":null,"work_id":"3aa1f2d9-0d6e-4dd7-9e83-778c1e2c07a9","year":2025},"citing_paper":{"arxiv_id":"2511.17652","last_updated":"2026-04-06T19:52:36Z","snapshot_observed_at":"2026-08-01T03:53:15.171510Z","submitted_at":"2025-11-20T13:29:35Z","title":"TeamPath: Building MultiModal Pathology Experts with Reasoning AI Copilots","version":2},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-05-17T20:29:39.744103Z"},"links":{"citing_paper":"/paper/2511.17652"},"observation_digest":"sha256:662f9b6f5c33c2e42d93cb5a0a41f54771eb91ba5abbcc10f4078e6ee1edb69d","observation_id":"f3bf449e-e68b-497a-a18d-5033fc9a57e3","resolution":{"observed_at":"2026-05-17T20:30:11.784605Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Analysis of 3d pathology samples using weakly supervised ai.Cell, 187(10):2502–2520","venue":null,"work_id":"c970c6dc-dd84-4c3f-bcc1-98d6afe6c150","year":2024},"citing_paper":{"arxiv_id":"2511.17652","last_updated":"2026-04-06T19:52:36Z","snapshot_observed_at":"2026-08-01T03:53:15.171510Z","submitted_at":"2025-11-20T13:29:35Z","title":"TeamPath: Building MultiModal Pathology Experts with Reasoning AI Copilots","version":2},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-05-17T20:29:39.744103Z"},"links":{"citing_paper":"/paper/2511.17652"},"observation_digest":"sha256:5ced09e869aed528dd7306e8b020f99baf364263aaa44b3e59b5d41228e48256","observation_id":"a45a9656-2679-4661-8b51-8dc72ea7a646","resolution":{"observed_at":"2026-05-17T20:30:11.786958Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Visium technology","venue":null,"work_id":"627ddaee-3832-49df-a08d-dff69529d698","year":null},"citing_paper":{"arxiv_id":"2511.17652","last_updated":"2026-04-06T19:52:36Z","snapshot_observed_at":"2026-08-01T03:53:15.171510Z","submitted_at":"2025-11-20T13:29:35Z","title":"TeamPath: Building MultiModal Pathology Experts with Reasoning AI Copilots","version":2},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-05-17T20:29:39.744103Z"},"links":{"citing_paper":"/paper/2511.17652"},"observation_digest":"sha256:e53ffedd76ec05b496967af7c1cbc7379a66e382c95648c07fe054dc3c23f86b","observation_id":"877590e9-17f8-4e7e-8bec-5337d2a5b29b","resolution":{"observed_at":"2026-05-17T20:30:11.845685Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Cell2sentence: Teaching largelanguagemodelsthelanguageofbiology","venue":null,"work_id":"29c450b5-b51b-4d75-872b-24b7cd15c884","year":2024},"citing_paper":{"arxiv_id":"2511.17652","last_updated":"2026-04-06T19:52:36Z","snapshot_observed_at":"2026-08-01T03:53:15.171510Z","submitted_at":"2025-11-20T13:29:35Z","title":"TeamPath: Building MultiModal Pathology Experts with Reasoning AI Copilots","version":2},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-05-17T20:29:39.744103Z"},"links":{"citing_paper":"/paper/2511.17652"},"observation_digest":"sha256:d888aa51cc9fe190540849b6e6bc2ff5e032d4e8ac1977d05af31d3dbc137b76","observation_id":"86b01789-5d52-4e40-98af-11af96e9e5bf","resolution":{"observed_at":"2026-05-17T20:30:11.763129Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2409.19256","last_updated":"2024-10-02T04:01:47Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-09-28T06:20:03Z","title":"HybridFlow: A Flexible and Efficient RLHF Framework","version":2},"cited_work":{"arxiv_id":"2409.19256","doi":"10.1145/3689031.3696075.url:","metadata_source":"pith","pith_arxiv_id":"2409.19256","snapshot_observed_at":"2026-07-11T11:50:26.030339Z","title":"HybridFlow: A Flexible and Efficient RLHF Framework","venue":"cs.LG","work_id":"7eb9c9f4-b322-4bba-8011-09ff8d6ad801","year":2024},"citing_paper":{"arxiv_id":"2511.17652","last_updated":"2026-04-06T19:52:36Z","snapshot_observed_at":"2026-08-01T03:53:15.171510Z","submitted_at":"2025-11-20T13:29:35Z","title":"TeamPath: Building MultiModal Pathology Experts with Reasoning AI Copilots","version":2},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-05-17T20:29:39.744103Z"},"links":{"cited_paper":"/paper/2409.19256","citing_paper":"/paper/2511.17652"},"observation_digest":"sha256:a9534606adce69a8415709061b72e98f4e5dbab337fc100b07d55b5cb30b8d03","observation_id":"8b34d167-b71f-4aa2-8616-95fa17f59de6","resolution":{"observed_at":"2026-05-17T20:30:11.107485Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"LlamaFactory: Unified efficient fine-tuning of 100+ language models","venue":null,"work_id":"6b0c6b49-ab5b-4b62-98b2-bead53b96e22","year":null},"citing_paper":{"arxiv_id":"2511.17652","last_updated":"2026-04-06T19:52:36Z","snapshot_observed_at":"2026-08-01T03:53:15.171510Z","submitted_at":"2025-11-20T13:29:35Z","title":"TeamPath: Building MultiModal Pathology Experts with Reasoning AI Copilots","version":2},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-05-17T20:29:39.744103Z"},"links":{"citing_paper":"/paper/2511.17652"},"observation_digest":"sha256:2f6e1ed0c999b38e64ffee56c4530f745246aa5b97bbd42552a935b49f2f76af","observation_id":"87e911e5-bef9-4271-8b03-ce0c489a9815","resolution":{"observed_at":"2026-05-17T20:30:11.768509Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-09T14:26:21.198691Z","title":null,"venue":null,"work_id":"c69dcc4d-85af-4249-accc-cbae1a0e230c","year":null},"citing_paper":{"arxiv_id":"2511.17652","last_updated":"2026-04-06T19:52:36Z","snapshot_observed_at":"2026-08-01T03:53:15.171510Z","submitted_at":"2025-11-20T13:29:35Z","title":"TeamPath: Building MultiModal Pathology Experts with Reasoning AI Copilots","version":2},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-05-17T20:29:39.744103Z"},"links":{"citing_paper":"/paper/2511.17652"},"observation_digest":"sha256:1173bd5649ea3b751824fd286f170107dd9d2f7de044312a7c5bbeb37ec56171","observation_id":"1fd95f6b-1843-47b2-b6fe-678a0daa9e3a","resolution":{"observed_at":"2026-05-17T20:30:11.765532Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2402.03300","last_updated":"2024-04-27T15:25:53Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-02-05T18:55:32Z","title":"DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models","version":3},"cited_work":{"arxiv_id":"2402.03300","doi":"10.1016/0004-3702(73)90011-8","metadata_source":"pith","pith_arxiv_id":"2402.03300","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models","venue":"cs.CL","work_id":"c5006563-f3ec-438a-9e35-b7b484f34828","year":2024},"citing_paper":{"arxiv_id":"2511.17652","last_updated":"2026-04-06T19:52:36Z","snapshot_observed_at":"2026-08-01T03:53:15.171510Z","submitted_at":"2025-11-20T13:29:35Z","title":"TeamPath: Building MultiModal Pathology Experts with Reasoning AI Copilots","version":2},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-05-17T20:29:39.744103Z"},"links":{"cited_paper":"/paper/2402.03300","citing_paper":"/paper/2511.17652"},"observation_digest":"sha256:46f250441d380c97682b6a2b6a985d95fbf01420a87106735aca373711e07349","observation_id":"0455cee5-961e-4bcb-bfc4-e118f91e7591","resolution":{"observed_at":"2026-05-17T20:30:11.156330Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2503.14476","last_updated":"2025-05-20T01:37:34Z","snapshot_observed_at":"2026-08-02T01:40:54.187278Z","submitted_at":"2025-03-18T17:49:06Z","title":"DAPO: An Open-Source LLM Reinforcement Learning System at Scale","version":2},"cited_work":{"arxiv_id":"2503.14476","doi":"10.48550/arxiv.2503.14476","metadata_source":"pith","pith_arxiv_id":"2503.14476","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"DAPO: An Open-Source LLM Reinforcement Learning System at Scale","venue":"cs.LG","work_id":"64019d00-0b11-4bbd-b173-b46c8fad0157","year":2025},"citing_paper":{"arxiv_id":"2511.17652","last_updated":"2026-04-06T19:52:36Z","snapshot_observed_at":"2026-08-01T03:53:15.171510Z","submitted_at":"2025-11-20T13:29:35Z","title":"TeamPath: Building MultiModal Pathology Experts with Reasoning AI Copilots","version":2},"reference_index":53,"source":"pdf_text","source_observed_at":"2026-05-17T20:29:39.744103Z"},"links":{"cited_paper":"/paper/2503.14476","citing_paper":"/paper/2511.17652"},"observation_digest":"sha256:cd896ccd2b91cd5fe54ddeb5f14588cd4cc71a828fb3631499ba049a5ea57058","observation_id":"0652fd76-8199-45b5-afc2-735d48feaf6b","resolution":{"observed_at":"2026-05-17T20:30:11.172348Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-05-24T09:23:06.254602+00:00","source":"crossref_status_cache"},{"observed_at":"2026-05-24T09:23:06.254602+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-08T09:34:48.099652Z","title":"Scikit- learn: Machine learning in python.the Journal of machine Learning research, 12:2825–2830","venue":null,"work_id":"176246e7-d671-481f-a25b-7f3341e00c8e","year":2011},"citing_paper":{"arxiv_id":"2511.17652","last_updated":"2026-04-06T19:52:36Z","snapshot_observed_at":"2026-08-01T03:53:15.171510Z","submitted_at":"2025-11-20T13:29:35Z","title":"TeamPath: Building MultiModal Pathology Experts with Reasoning AI Copilots","version":2},"reference_index":54,"source":"pdf_text","source_observed_at":"2026-05-17T20:29:39.744103Z"},"links":{"citing_paper":"/paper/2511.17652"},"observation_digest":"sha256:330a8e530813028c9f1944adae803ddda5463621968063c43ce19c7ce2fb5fb6","observation_id":"735a828e-c7d6-4237-a9db-4fc798cdfe7b","resolution":{"observed_at":"2026-05-17T20:30:11.760939Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Scipy 1.0: fundamental algorithms for scientific computing in python.Nature methods, 17(3):261–272","venue":null,"work_id":"3cc26fb0-6d2a-44e2-91fe-5fcd44aca9d0","year":2020},"citing_paper":{"arxiv_id":"2511.17652","last_updated":"2026-04-06T19:52:36Z","snapshot_observed_at":"2026-08-01T03:53:15.171510Z","submitted_at":"2025-11-20T13:29:35Z","title":"TeamPath: Building MultiModal Pathology Experts with Reasoning AI Copilots","version":2},"reference_index":55,"source":"pdf_text","source_observed_at":"2026-05-17T20:29:39.744103Z"},"links":{"citing_paper":"/paper/2511.17652"},"observation_digest":"sha256:dc8bb864187c29ba341dd1f1531b04b14461da1705a8d9f7cc9ef82cd64b576f","observation_id":"17909f9b-2d53-458e-842c-a597c51aab94","resolution":{"observed_at":"2026-05-17T20:30:11.782405Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Radgraph: Extracting clinical entities and relations from radiology reports","venue":null,"work_id":"377eae64-f3f5-47e9-bb9c-4769d9d697d7","year":null},"citing_paper":{"arxiv_id":"2511.17652","last_updated":"2026-04-06T19:52:36Z","snapshot_observed_at":"2026-08-01T03:53:15.171510Z","submitted_at":"2025-11-20T13:29:35Z","title":"TeamPath: Building MultiModal Pathology Experts with Reasoning AI Copilots","version":2},"reference_index":56,"source":"pdf_text","source_observed_at":"2026-05-17T20:29:39.744103Z"},"links":{"citing_paper":"/paper/2511.17652"},"observation_digest":"sha256:c51afb92d1eff6f5dd79f8f903f798db3a8d08c8ccc7c83cec77b7d4d40470a2","observation_id":"0e14ebc9-a3d0-4af5-857b-8d0799a463e2","resolution":{"observed_at":"2026-05-17T20:30:11.779953Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Aci-bench: a novel ambient clinical intelligence dataset for benchmarking automatic visit note generation.Scientific Data, 10(1):586","venue":null,"work_id":"58e3ca3e-5db7-44f7-b0f5-156f934a6968","year":2023},"citing_paper":{"arxiv_id":"2511.17652","last_updated":"2026-04-06T19:52:36Z","snapshot_observed_at":"2026-08-01T03:53:15.171510Z","submitted_at":"2025-11-20T13:29:35Z","title":"TeamPath: Building MultiModal Pathology Experts with Reasoning AI Copilots","version":2},"reference_index":57,"source":"pdf_text","source_observed_at":"2026-05-17T20:29:39.744103Z"},"links":{"citing_paper":"/paper/2511.17652"},"observation_digest":"sha256:de9202aaa23ccc3d5d09e358f12b636df04c08ef68899b871b6c32f495677d40","observation_id":"c2a32a7c-a4c8-47cd-9bf4-6a1921e5c53b","resolution":{"observed_at":"2026-05-17T20:30:11.791248Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Adapted large language models can outperform medical experts in clinical text summarization","venue":null,"work_id":"625cc49f-c8f9-4e93-9d86-38f8f7329fdb","year":2024},"citing_paper":{"arxiv_id":"2511.17652","last_updated":"2026-04-06T19:52:36Z","snapshot_observed_at":"2026-08-01T03:53:15.171510Z","submitted_at":"2025-11-20T13:29:35Z","title":"TeamPath: Building MultiModal Pathology Experts with Reasoning AI Copilots","version":2},"reference_index":58,"source":"pdf_text","source_observed_at":"2026-05-17T20:29:39.744103Z"},"links":{"citing_paper":"/paper/2511.17652"},"observation_digest":"sha256:746bdedfe58037b60623cfdbaa6e3eac60203e17270561e32cc702da1cd1d133","observation_id":"eb7bfc1c-b124-48dc-a0b1-9dfd37d445ef","resolution":{"observed_at":"2026-05-17T20:30:11.770605Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Visualinstructiontuning.Advances in neural information processing systems, 36:34892–34916","venue":null,"work_id":"0147738a-c452-454e-a83f-5b00d0dcca58","year":2023},"citing_paper":{"arxiv_id":"2511.17652","last_updated":"2026-04-06T19:52:36Z","snapshot_observed_at":"2026-08-01T03:53:15.171510Z","submitted_at":"2025-11-20T13:29:35Z","title":"TeamPath: Building MultiModal Pathology Experts with Reasoning AI Copilots","version":2},"reference_index":59,"source":"pdf_text","source_observed_at":"2026-05-17T20:29:39.744103Z"},"links":{"citing_paper":"/paper/2511.17652"},"observation_digest":"sha256:ffce493b9dcf17b366c341586f928cb22b890b894c080b087445b99adde74343","observation_id":"d21dd540-0ddd-4a7a-8910-eb19dfc52396","resolution":{"observed_at":"2026-05-17T20:30:11.772665Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2506.06122","last_updated":"2025-06-06T14:33:56Z","snapshot_observed_at":"2026-07-06T21:37:56.477028Z","submitted_at":"2025-06-06T14:33:56Z","title":"Reinforcement Learning Optimization for Large-Scale Learning: An Efficient and User-Friendly Scaling Library","version":1},"cited_work":{"arxiv_id":"2506.06122","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2506.06122","snapshot_observed_at":"2026-07-04T10:29:45.796847Z","title":"Reinforcement learning optimization for large-scale learning: An efficient and user-friendly scaling library.arXiv preprint arXiv:2506.06122, 2025a","venue":null,"work_id":"37914127-0152-4730-8654-8b15734bd5f9","year":2025},"citing_paper":{"arxiv_id":"2511.17652","last_updated":"2026-04-06T19:52:36Z","snapshot_observed_at":"2026-08-01T03:53:15.171510Z","submitted_at":"2025-11-20T13:29:35Z","title":"TeamPath: Building MultiModal Pathology Experts with Reasoning AI Copilots","version":2},"reference_index":60,"source":"pdf_text","source_observed_at":"2026-05-17T20:29:39.744103Z"},"links":{"cited_paper":"/paper/2506.06122","citing_paper":"/paper/2511.17652"},"observation_digest":"sha256:98e3adf733d1925edb9e56fc056f85e545db8d861aaed3c97113a5ff5e7c535a","observation_id":"e0190bf3-ac8c-4976-b820-cf6851901b3d","resolution":{"observed_at":"2026-05-17T20:30:11.134883Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2508.08221","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-07-04T09:09:43.596767Z","title":"Part i: Tricks or traps? a deep dive into rl for llm reasoning","venue":null,"work_id":"e0435aed-9cb6-435b-bb39-63bfca8ed5bd","year":2025},"citing_paper":{"arxiv_id":"2511.17652","last_updated":"2026-04-06T19:52:36Z","snapshot_observed_at":"2026-08-01T03:53:15.171510Z","submitted_at":"2025-11-20T13:29:35Z","title":"TeamPath: Building MultiModal Pathology Experts with Reasoning AI Copilots","version":2},"reference_index":61,"source":"pdf_text","source_observed_at":"2026-05-17T20:29:39.744103Z"},"links":{"citing_paper":"/paper/2511.17652"},"observation_digest":"sha256:5195ec7ac6a577085da85fe8b38c722015dc5cd59ce496d675ecc162bc083576","observation_id":"4104e248-36d5-4c61-b19b-a4f6936dc510","resolution":{"observed_at":"2026-05-17T20:30:11.160442Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2504.11468","last_updated":"2025-04-10T16:54:05Z","snapshot_observed_at":"2026-08-05T02:57:13.928237Z","submitted_at":"2025-04-10T16:54:05Z","title":"SFT or RL? An Early Investigation into Training R1-Like Reasoning Large Vision-Language Models","version":1},"cited_work":{"arxiv_id":"2504.11468","doi":"10.48550/arxiv.2504.11468","metadata_source":"pith","pith_arxiv_id":"2504.11468","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"SFT or RL? An Early Investigation into Training R1-Like Reasoning Large Vision-Language Models","venue":"cs.CL","work_id":"a521360c-8673-4d0d-a3a3-6eb9f7a71b90","year":2025},"citing_paper":{"arxiv_id":"2511.17652","last_updated":"2026-04-06T19:52:36Z","snapshot_observed_at":"2026-08-01T03:53:15.171510Z","submitted_at":"2025-11-20T13:29:35Z","title":"TeamPath: Building MultiModal Pathology Experts with Reasoning AI Copilots","version":2},"reference_index":62,"source":"pdf_text","source_observed_at":"2026-05-17T20:29:39.744103Z"},"links":{"cited_paper":"/paper/2504.11468","citing_paper":"/paper/2511.17652"},"observation_digest":"sha256:7c55cb4401375a41b2c3d83d199a52c882ab52c8c9080c551947c37a2af670ef","observation_id":"6f0c7d33-ee0b-4908-8407-12343980bcf5","resolution":{"observed_at":"2026-05-17T20:30:11.116491Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":"2508.11408","doi":"10.48550/arxiv.2508.11408","metadata_source":"arxiv_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"arXiv preprint arXiv:2508.11408 , year=","venue":"arXiv (Cornell University)","work_id":"994df3c4-5dc6-45c0-9db5-e82e415ce5d8","year":2025},"citing_paper":{"arxiv_id":"2511.17652","last_updated":"2026-04-06T19:52:36Z","snapshot_observed_at":"2026-08-01T03:53:15.171510Z","submitted_at":"2025-11-20T13:29:35Z","title":"TeamPath: Building MultiModal Pathology Experts with Reasoning AI Copilots","version":2},"reference_index":63,"source":"pdf_text","source_observed_at":"2026-05-17T20:29:39.744103Z"},"links":{"citing_paper":"/paper/2511.17652"},"observation_digest":"sha256:852408a8db6fa48b534a014bd3041b285f72e57dc4eed33da6088e6ae001e75c","observation_id":"97c674a9-d573-4b13-9f73-a70f64d2ec4a","resolution":{"observed_at":"2026-05-17T20:30:11.125071Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2511.17652","last_updated":"2026-04-06T19:52:36Z","latest_version":2,"primary_category":"q-bio.QM","snapshot_observed_at":"2026-08-01T03:53:15.171510Z","submitted_at":"2025-11-20T13:29:35Z","title":"TeamPath: Building MultiModal Pathology Experts with Reasoning AI Copilots"},"reference_resolution":{"displayed":63,"state_counts":{"malformed_identifier":0,"metadata_mismatch":1,"parse_uncertain":0,"unresolved":1,"verified_exact":21,"verified_fuzzy":40},"total_outbound_references":63},"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":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"thesis":"As of 6 August 2026, this Paper Citation Record lists 63 of 63 outbound references and 4 inbound Pith citation observations for arXiv:2511.17652."}