{"as_of":"2026-08-08T20:05:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:e44012db55574eac8c64a0e6aedbde4142a897d8d4154bd08555b69ac56a05be","coverage":[{"denominator":90,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":90,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-01T02:21:23.281512Z","state":"measured"},{"denominator":90,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":90,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-08T06:32:00.761636+00:00","state":"measured"},{"denominator":0,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[],"links":{"evidence":"/evidence","html":"/paper/2607.25485/citation-record","integrity":"/paper/2607.25485/integrity","json":"/paper/2607.25485/citation-record.json","paper":"/paper/2607.25485"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T02:21:17.996665Z","title":"2001 , publisher =","venue":null,"work_id":null,"year":2001},"citing_paper":{"arxiv_id":"2607.25485","last_updated":"2026-07-28T09:24:04Z","snapshot_observed_at":"2026-08-08T05:57:13.194969Z","submitted_at":"2026-07-28T09:24:04Z","title":"PatientAgentBench: A Benchmark Framework for Evaluating Patient-Facing Health AI Agents","version":1},"reference_index":1,"source":"arxiv_source","source_observed_at":"2026-08-01T02:21:17.996665Z"},"links":{"citing_paper":"/paper/2607.25485"},"observation_digest":"sha256:678490d368538d514f9b4dab8c7267d7d81268a2c7775b0a8337a631ffbbd107","observation_id":"3766f1de-5153-41a0-9f76-2114a82dc3f9","resolution":{"observed_at":"2026-08-01T02:21:17.996665Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T02:21:18.069957Z","title":"2021 , url =","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2607.25485","last_updated":"2026-07-28T09:24:04Z","snapshot_observed_at":"2026-08-08T05:57:13.194969Z","submitted_at":"2026-07-28T09:24:04Z","title":"PatientAgentBench: A Benchmark Framework for Evaluating Patient-Facing Health AI Agents","version":1},"reference_index":2,"source":"arxiv_source","source_observed_at":"2026-08-01T02:21:18.069957Z"},"links":{"citing_paper":"/paper/2607.25485"},"observation_digest":"sha256:8e206208dec32cfe63900b4bb7604daf66e58b425bee08660bd4399aba0ba164","observation_id":"5ed8be90-8cd6-4524-a1ca-f98a0bdf0cbe","resolution":{"observed_at":"2026-08-01T02:21:18.069957Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T02:21:18.148970Z","title":"2022 , note =","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2607.25485","last_updated":"2026-07-28T09:24:04Z","snapshot_observed_at":"2026-08-08T05:57:13.194969Z","submitted_at":"2026-07-28T09:24:04Z","title":"PatientAgentBench: A Benchmark Framework for Evaluating Patient-Facing Health AI Agents","version":1},"reference_index":3,"source":"arxiv_source","source_observed_at":"2026-08-01T02:21:18.148970Z"},"links":{"citing_paper":"/paper/2607.25485"},"observation_digest":"sha256:ff7c155b8848d2271d34cbca0845ef3076ac4dde86d2c3eb6743d0e07be97302","observation_id":"1afb11b6-a59a-48e2-b58e-8303e11fa8d5","resolution":{"observed_at":"2026-08-01T02:21:18.148970Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T02:21:18.249494Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.25485","last_updated":"2026-07-28T09:24:04Z","snapshot_observed_at":"2026-08-08T05:57:13.194969Z","submitted_at":"2026-07-28T09:24:04Z","title":"PatientAgentBench: A Benchmark Framework for Evaluating Patient-Facing Health AI Agents","version":1},"reference_index":4,"source":"arxiv_source","source_observed_at":"2026-08-01T02:21:18.249494Z"},"links":{"citing_paper":"/paper/2607.25485"},"observation_digest":"sha256:566ed826f965ff84ab88e67da3c8ee11e779e978cfee3fa986b3b818a59a7c3c","observation_id":"4aabc5c4-edab-4321-a214-5471f0c5f490","resolution":{"observed_at":"2026-08-01T02:21:18.249494Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T02:21:18.327124Z","title":"BMJ Quality & Safety , volume =","venue":null,"work_id":null,"year":2017},"citing_paper":{"arxiv_id":"2607.25485","last_updated":"2026-07-28T09:24:04Z","snapshot_observed_at":"2026-08-08T05:57:13.194969Z","submitted_at":"2026-07-28T09:24:04Z","title":"PatientAgentBench: A Benchmark Framework for Evaluating Patient-Facing Health AI Agents","version":1},"reference_index":5,"source":"arxiv_source","source_observed_at":"2026-08-01T02:21:18.327124Z"},"links":{"citing_paper":"/paper/2607.25485"},"observation_digest":"sha256:b255c15bb76048e957cbed9bdf307337afd868d146c6e0933899059742a6bacb","observation_id":"c82ab66f-a41e-4d8b-9e56-33f1f51c5570","resolution":{"observed_at":"2026-08-01T02:21:18.327124Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T02:21:18.401279Z","title":"2023 , howpublished =","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.25485","last_updated":"2026-07-28T09:24:04Z","snapshot_observed_at":"2026-08-08T05:57:13.194969Z","submitted_at":"2026-07-28T09:24:04Z","title":"PatientAgentBench: A Benchmark Framework for Evaluating Patient-Facing Health AI Agents","version":1},"reference_index":6,"source":"arxiv_source","source_observed_at":"2026-08-01T02:21:18.401279Z"},"links":{"citing_paper":"/paper/2607.25485"},"observation_digest":"sha256:8e308875182317c872b3862ae0b8292c07628268cac6789911f4b83fef769546","observation_id":"a54b7eb0-1321-436b-87ec-04e7062fadd2","resolution":{"observed_at":"2026-08-01T02:21:18.401279Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T02:21:18.556940Z","title":"2015 , publisher =","venue":null,"work_id":null,"year":2015},"citing_paper":{"arxiv_id":"2607.25485","last_updated":"2026-07-28T09:24:04Z","snapshot_observed_at":"2026-08-08T05:57:13.194969Z","submitted_at":"2026-07-28T09:24:04Z","title":"PatientAgentBench: A Benchmark Framework for Evaluating Patient-Facing Health AI Agents","version":1},"reference_index":7,"source":"arxiv_source","source_observed_at":"2026-08-01T02:21:18.556940Z"},"links":{"citing_paper":"/paper/2607.25485"},"observation_digest":"sha256:c949a3bc00aec45cb8503d7084d3a54f50005017bee16e98f369651043f68455","observation_id":"d6f90ebe-28b7-42cf-80bf-7718e915c2c6","resolution":{"observed_at":"2026-08-01T02:21:18.556940Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2604.27470","last_updated":"2026-04-30T06:13:01Z","snapshot_observed_at":"2026-07-06T23:12:57.730833Z","submitted_at":"2026-04-30T06:13:01Z","title":"HealthBench Professional: Evaluating Large Language Models on Real Clinician Chats","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2604.27470","snapshot_observed_at":"2026-08-01T02:21:18.679824Z","title":"arXiv preprint arXiv:2604.27470 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.25485","last_updated":"2026-07-28T09:24:04Z","snapshot_observed_at":"2026-08-08T05:57:13.194969Z","submitted_at":"2026-07-28T09:24:04Z","title":"PatientAgentBench: A Benchmark Framework for Evaluating Patient-Facing Health AI Agents","version":1},"reference_index":8,"source":"arxiv_source","source_observed_at":"2026-08-01T02:21:18.679824Z"},"links":{"cited_paper":"/paper/2604.27470","citing_paper":"/paper/2607.25485"},"observation_digest":"sha256:eb5cc05d84239ee27ce6e61f5e9fc823227167fd0a9d7def6c3f1bbaef5e83ce","observation_id":"2d6fbe6c-a523-440f-afa9-0bbbdded1c0b","resolution":{"observed_at":"2026-08-01T02:21:18.679824Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T02:21:18.739263Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.25485","last_updated":"2026-07-28T09:24:04Z","snapshot_observed_at":"2026-08-08T05:57:13.194969Z","submitted_at":"2026-07-28T09:24:04Z","title":"PatientAgentBench: A Benchmark Framework for Evaluating Patient-Facing Health AI Agents","version":1},"reference_index":9,"source":"arxiv_source","source_observed_at":"2026-08-01T02:21:18.739263Z"},"links":{"citing_paper":"/paper/2607.25485"},"observation_digest":"sha256:fc76ede967da1255f5925ce8d2a3cf729e0e76e9f4176f487dd795dfe6358840","observation_id":"5133b7e0-ecc1-411a-8ae2-c76bb59ada90","resolution":{"observed_at":"2026-08-01T02:21:18.739263Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T02:21:18.871029Z","title":"2024 , url=","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.25485","last_updated":"2026-07-28T09:24:04Z","snapshot_observed_at":"2026-08-08T05:57:13.194969Z","submitted_at":"2026-07-28T09:24:04Z","title":"PatientAgentBench: A Benchmark Framework for Evaluating Patient-Facing Health AI Agents","version":1},"reference_index":10,"source":"arxiv_source","source_observed_at":"2026-08-01T02:21:18.871029Z"},"links":{"citing_paper":"/paper/2607.25485"},"observation_digest":"sha256:3ec895d6c6e89082ed487b8dce348b1d215e3142dea5fbcd8586d45c1049f4cc","observation_id":"82dc9853-a72c-41d4-9b8e-5c731005aeaf","resolution":{"observed_at":"2026-08-01T02:21:18.871029Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T02:21:18.895834Z","title":", journal=","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.25485","last_updated":"2026-07-28T09:24:04Z","snapshot_observed_at":"2026-08-08T05:57:13.194969Z","submitted_at":"2026-07-28T09:24:04Z","title":"PatientAgentBench: A Benchmark Framework for Evaluating Patient-Facing Health AI Agents","version":1},"reference_index":11,"source":"arxiv_source","source_observed_at":"2026-08-01T02:21:18.895834Z"},"links":{"citing_paper":"/paper/2607.25485"},"observation_digest":"sha256:c56f18c00ff2b8c1230c836d9b8fcedab456dcbb20ce117c197e4e8f8f482b0d","observation_id":"b8540d1f-2cf4-4128-a553-661017145689","resolution":{"observed_at":"2026-08-01T02:21:18.895834Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T02:21:18.977740Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.25485","last_updated":"2026-07-28T09:24:04Z","snapshot_observed_at":"2026-08-08T05:57:13.194969Z","submitted_at":"2026-07-28T09:24:04Z","title":"PatientAgentBench: A Benchmark Framework for Evaluating Patient-Facing Health AI Agents","version":1},"reference_index":12,"source":"arxiv_source","source_observed_at":"2026-08-01T02:21:18.977740Z"},"links":{"citing_paper":"/paper/2607.25485"},"observation_digest":"sha256:d7214c598f5a0e5bf6cafcb3f4e0b9bf23ab015854f7664970f25c39a2f2ee95","observation_id":"5145c540-da71-4c6a-a9a6-581558ec44e3","resolution":{"observed_at":"2026-08-01T02:21:18.977740Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T02:21:19.053604Z","title":"npj Digital Medicine , volume=","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2607.25485","last_updated":"2026-07-28T09:24:04Z","snapshot_observed_at":"2026-08-08T05:57:13.194969Z","submitted_at":"2026-07-28T09:24:04Z","title":"PatientAgentBench: A Benchmark Framework for Evaluating Patient-Facing Health AI Agents","version":1},"reference_index":13,"source":"arxiv_source","source_observed_at":"2026-08-01T02:21:19.053604Z"},"links":{"citing_paper":"/paper/2607.25485"},"observation_digest":"sha256:4687e374eeff557631342cb27da350ad529856ebee1e3a6618650b580ad7260c","observation_id":"e2b3a5c0-21ca-4b6b-b4da-62c8126118a7","resolution":{"observed_at":"2026-08-01T02:21:19.053604Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T02:21:19.137495Z","title":"Nature Biomedical Engineering , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.25485","last_updated":"2026-07-28T09:24:04Z","snapshot_observed_at":"2026-08-08T05:57:13.194969Z","submitted_at":"2026-07-28T09:24:04Z","title":"PatientAgentBench: A Benchmark Framework for Evaluating Patient-Facing Health AI Agents","version":1},"reference_index":14,"source":"arxiv_source","source_observed_at":"2026-08-01T02:21:19.137495Z"},"links":{"citing_paper":"/paper/2607.25485"},"observation_digest":"sha256:1d3ce72abe8939fb604d6866b139b486d15a43c2a255abe8c21cf5cc36162be3","observation_id":"2ddafd12-fac0-4475-94fc-0131f2e7749b","resolution":{"observed_at":"2026-08-01T02:21:19.137495Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T02:21:19.237080Z","title":"NPJ Digital Medicine , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.25485","last_updated":"2026-07-28T09:24:04Z","snapshot_observed_at":"2026-08-08T05:57:13.194969Z","submitted_at":"2026-07-28T09:24:04Z","title":"PatientAgentBench: A Benchmark Framework for Evaluating Patient-Facing Health AI Agents","version":1},"reference_index":15,"source":"arxiv_source","source_observed_at":"2026-08-01T02:21:19.237080Z"},"links":{"citing_paper":"/paper/2607.25485"},"observation_digest":"sha256:9fd794659c269bfc6a37388551ef6e96a9606b0cab8a3f48878b6a0457dda772","observation_id":"572748a5-1d98-47a9-b633-b3312eebc609","resolution":{"observed_at":"2026-08-01T02:21:19.237080Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T02:21:19.280290Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.25485","last_updated":"2026-07-28T09:24:04Z","snapshot_observed_at":"2026-08-08T05:57:13.194969Z","submitted_at":"2026-07-28T09:24:04Z","title":"PatientAgentBench: A Benchmark Framework for Evaluating Patient-Facing Health AI Agents","version":1},"reference_index":16,"source":"arxiv_source","source_observed_at":"2026-08-01T02:21:19.280290Z"},"links":{"citing_paper":"/paper/2607.25485"},"observation_digest":"sha256:8fd26d34b57c18405a78b7da31186163c113c77300a0998bc1e3dabec2db2365","observation_id":"4340bb15-0dbd-49fc-b6d7-07cf854f9fd7","resolution":{"observed_at":"2026-08-01T02:21:19.280290Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T02:21:19.358934Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.25485","last_updated":"2026-07-28T09:24:04Z","snapshot_observed_at":"2026-08-08T05:57:13.194969Z","submitted_at":"2026-07-28T09:24:04Z","title":"PatientAgentBench: A Benchmark Framework for Evaluating Patient-Facing Health AI Agents","version":1},"reference_index":17,"source":"arxiv_source","source_observed_at":"2026-08-01T02:21:19.358934Z"},"links":{"citing_paper":"/paper/2607.25485"},"observation_digest":"sha256:b453f0cabedd00bf16497537301c4f965123d28ccda2c7f8f041f105d8b4de31","observation_id":"84c1942a-39a1-4798-ba74-105204196ce2","resolution":{"observed_at":"2026-08-01T02:21:19.358934Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T02:21:19.448307Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.25485","last_updated":"2026-07-28T09:24:04Z","snapshot_observed_at":"2026-08-08T05:57:13.194969Z","submitted_at":"2026-07-28T09:24:04Z","title":"PatientAgentBench: A Benchmark Framework for Evaluating Patient-Facing Health AI Agents","version":1},"reference_index":18,"source":"arxiv_source","source_observed_at":"2026-08-01T02:21:19.448307Z"},"links":{"citing_paper":"/paper/2607.25485"},"observation_digest":"sha256:6eb95953402398d0e8a361f5e308083d30d39b97cce2d721e330f0828b9b18bc","observation_id":"12ff1d21-88bf-4091-90ef-80a748d623ae","resolution":{"observed_at":"2026-08-01T02:21:19.448307Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T02:21:19.510948Z","title":"Patient Education and Counseling , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.25485","last_updated":"2026-07-28T09:24:04Z","snapshot_observed_at":"2026-08-08T05:57:13.194969Z","submitted_at":"2026-07-28T09:24:04Z","title":"PatientAgentBench: A Benchmark Framework for Evaluating Patient-Facing Health AI Agents","version":1},"reference_index":19,"source":"arxiv_source","source_observed_at":"2026-08-01T02:21:19.510948Z"},"links":{"citing_paper":"/paper/2607.25485"},"observation_digest":"sha256:db287d83906078762fe91fd62e30319bda8954eee4614918b0faa31da0f31b1e","observation_id":"2b6e8cb1-25a5-40c3-b37c-a349317de069","resolution":{"observed_at":"2026-08-01T02:21:19.510948Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T02:21:19.606673Z","title":"BMJ , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.25485","last_updated":"2026-07-28T09:24:04Z","snapshot_observed_at":"2026-08-08T05:57:13.194969Z","submitted_at":"2026-07-28T09:24:04Z","title":"PatientAgentBench: A Benchmark Framework for Evaluating Patient-Facing Health AI Agents","version":1},"reference_index":20,"source":"arxiv_source","source_observed_at":"2026-08-01T02:21:19.606673Z"},"links":{"citing_paper":"/paper/2607.25485"},"observation_digest":"sha256:8fa6cda770428b336bd6f766511ddbd99ca34c83853f955b18132e787ba6ba3c","observation_id":"6a204367-a294-4bf0-bad3-e84c670ff169","resolution":{"observed_at":"2026-08-01T02:21:19.606673Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T02:21:19.660341Z","title":"Nature Medicine , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.25485","last_updated":"2026-07-28T09:24:04Z","snapshot_observed_at":"2026-08-08T05:57:13.194969Z","submitted_at":"2026-07-28T09:24:04Z","title":"PatientAgentBench: A Benchmark Framework for Evaluating Patient-Facing Health AI Agents","version":1},"reference_index":21,"source":"arxiv_source","source_observed_at":"2026-08-01T02:21:19.660341Z"},"links":{"citing_paper":"/paper/2607.25485"},"observation_digest":"sha256:c1004a18919ef974aad1c6c0dbff47f0612c5782031bb7498bfc7394d01432db","observation_id":"e595d080-e486-42c3-a7f9-d943664b6795","resolution":{"observed_at":"2026-08-01T02:21:19.660341Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T02:21:19.766031Z","title":"Artificial Intelligence Review , volume=","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.25485","last_updated":"2026-07-28T09:24:04Z","snapshot_observed_at":"2026-08-08T05:57:13.194969Z","submitted_at":"2026-07-28T09:24:04Z","title":"PatientAgentBench: A Benchmark Framework for Evaluating Patient-Facing Health AI Agents","version":1},"reference_index":22,"source":"arxiv_source","source_observed_at":"2026-08-01T02:21:19.766031Z"},"links":{"citing_paper":"/paper/2607.25485"},"observation_digest":"sha256:1e79fc9535fc9b1b5171226fc07b580783bda6e3eff2a0ef0de9a41391044dd9","observation_id":"4e189cb0-cdc7-47e4-a618-48d48e14c39e","resolution":{"observed_at":"2026-08-01T02:21:19.766031Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T02:21:19.788320Z","title":"JAMA , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.25485","last_updated":"2026-07-28T09:24:04Z","snapshot_observed_at":"2026-08-08T05:57:13.194969Z","submitted_at":"2026-07-28T09:24:04Z","title":"PatientAgentBench: A Benchmark Framework for Evaluating Patient-Facing Health AI Agents","version":1},"reference_index":23,"source":"arxiv_source","source_observed_at":"2026-08-01T02:21:19.788320Z"},"links":{"citing_paper":"/paper/2607.25485"},"observation_digest":"sha256:e001da351c897431b5b373ae05a3bf333d7794da3b1e95217a9e009be265e17e","observation_id":"5bfc97ef-4af7-49d9-bd9e-a2d335722588","resolution":{"observed_at":"2026-08-01T02:21:19.788320Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T02:21:19.865287Z","title":"Nature , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.25485","last_updated":"2026-07-28T09:24:04Z","snapshot_observed_at":"2026-08-08T05:57:13.194969Z","submitted_at":"2026-07-28T09:24:04Z","title":"PatientAgentBench: A Benchmark Framework for Evaluating Patient-Facing Health AI Agents","version":1},"reference_index":24,"source":"arxiv_source","source_observed_at":"2026-08-01T02:21:19.865287Z"},"links":{"citing_paper":"/paper/2607.25485"},"observation_digest":"sha256:7b0ce06191d95b3e58c2773c6fbdefbb4b326d38fd6d581eb3aea7f720373015","observation_id":"7fdc98d7-198d-4182-a7e4-758b084326f3","resolution":{"observed_at":"2026-08-01T02:21:19.865287Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T02:21:19.921549Z","title":"NEJM AI , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.25485","last_updated":"2026-07-28T09:24:04Z","snapshot_observed_at":"2026-08-08T05:57:13.194969Z","submitted_at":"2026-07-28T09:24:04Z","title":"PatientAgentBench: A Benchmark Framework for Evaluating Patient-Facing Health AI Agents","version":1},"reference_index":25,"source":"arxiv_source","source_observed_at":"2026-08-01T02:21:19.921549Z"},"links":{"citing_paper":"/paper/2607.25485"},"observation_digest":"sha256:a5eb177f17cdbc1409c6a17b2e64d03ea0735e3b43aed330dfcb558e015e0a1b","observation_id":"cedf752f-0159-4c4a-ad6e-dfc543addee8","resolution":{"observed_at":"2026-08-01T02:21:19.921549Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T02:21:19.974313Z","title":"Science , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.25485","last_updated":"2026-07-28T09:24:04Z","snapshot_observed_at":"2026-08-08T05:57:13.194969Z","submitted_at":"2026-07-28T09:24:04Z","title":"PatientAgentBench: A Benchmark Framework for Evaluating Patient-Facing Health AI Agents","version":1},"reference_index":26,"source":"arxiv_source","source_observed_at":"2026-08-01T02:21:19.974313Z"},"links":{"citing_paper":"/paper/2607.25485"},"observation_digest":"sha256:ea473ee2173c4bd5c0901061f65df5639a34ba97fe84e652df42305bc39cb0a7","observation_id":"7271ba60-670a-4192-a716-d03538f15416","resolution":{"observed_at":"2026-08-01T02:21:19.974313Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T02:21:20.031170Z","title":"The Lancet Digital Health , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.25485","last_updated":"2026-07-28T09:24:04Z","snapshot_observed_at":"2026-08-08T05:57:13.194969Z","submitted_at":"2026-07-28T09:24:04Z","title":"PatientAgentBench: A Benchmark Framework for Evaluating Patient-Facing Health AI Agents","version":1},"reference_index":27,"source":"arxiv_source","source_observed_at":"2026-08-01T02:21:20.031170Z"},"links":{"citing_paper":"/paper/2607.25485"},"observation_digest":"sha256:09304e6b8c513c75d64f4269dfba3ed0ad5f2242f9ec7b17bb5d4a1b941c3f01","observation_id":"771c716b-d1dd-45b6-b0ac-f1a3ae886674","resolution":{"observed_at":"2026-08-01T02:21:20.031170Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T02:21:20.121386Z","title":"NPJ Digital Medicine , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.25485","last_updated":"2026-07-28T09:24:04Z","snapshot_observed_at":"2026-08-08T05:57:13.194969Z","submitted_at":"2026-07-28T09:24:04Z","title":"PatientAgentBench: A Benchmark Framework for Evaluating Patient-Facing Health AI Agents","version":1},"reference_index":28,"source":"arxiv_source","source_observed_at":"2026-08-01T02:21:20.121386Z"},"links":{"citing_paper":"/paper/2607.25485"},"observation_digest":"sha256:03ef25163779326c8e86f6f4c404aa36fa811f646e7fc6bbea46327f2d4a56c4","observation_id":"aed0c3c7-2485-448e-900e-c406ac43fea6","resolution":{"observed_at":"2026-08-01T02:21:20.121386Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T02:21:20.170241Z","title":"Journal of the American Medical Informatics Association , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.25485","last_updated":"2026-07-28T09:24:04Z","snapshot_observed_at":"2026-08-08T05:57:13.194969Z","submitted_at":"2026-07-28T09:24:04Z","title":"PatientAgentBench: A Benchmark Framework for Evaluating Patient-Facing Health AI Agents","version":1},"reference_index":29,"source":"arxiv_source","source_observed_at":"2026-08-01T02:21:20.170241Z"},"links":{"citing_paper":"/paper/2607.25485"},"observation_digest":"sha256:78728009ce35fecb40c2bad90e2c5e869619181e221137201e27508cbe526bc1","observation_id":"c47e663e-93b1-4917-ac52-efc274eba4ab","resolution":{"observed_at":"2026-08-01T02:21:20.170241Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T02:21:20.229275Z","title":"Health Affairs , volume=","venue":null,"work_id":null,"year":2010},"citing_paper":{"arxiv_id":"2607.25485","last_updated":"2026-07-28T09:24:04Z","snapshot_observed_at":"2026-08-08T05:57:13.194969Z","submitted_at":"2026-07-28T09:24:04Z","title":"PatientAgentBench: A Benchmark Framework for Evaluating Patient-Facing Health AI Agents","version":1},"reference_index":30,"source":"arxiv_source","source_observed_at":"2026-08-01T02:21:20.229275Z"},"links":{"citing_paper":"/paper/2607.25485"},"observation_digest":"sha256:a37aa33358882c3f755cfe52d02aa8eca249eec5e05b0884255730c3a6c6b836","observation_id":"dd80af87-8579-4405-b175-98d7cf812c7d","resolution":{"observed_at":"2026-08-01T02:21:20.229275Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T02:21:20.304733Z","title":"2007 , doi=","venue":null,"work_id":null,"year":2007},"citing_paper":{"arxiv_id":"2607.25485","last_updated":"2026-07-28T09:24:04Z","snapshot_observed_at":"2026-08-08T05:57:13.194969Z","submitted_at":"2026-07-28T09:24:04Z","title":"PatientAgentBench: A Benchmark Framework for Evaluating Patient-Facing Health AI Agents","version":1},"reference_index":31,"source":"arxiv_source","source_observed_at":"2026-08-01T02:21:20.304733Z"},"links":{"citing_paper":"/paper/2607.25485"},"observation_digest":"sha256:2f5060d9e56bc5e3ebe28c63e5757179d24c1fab5c420eecc5ce0a47fd331181","observation_id":"7a43b0ee-7c2f-4355-8db6-767ef1df19bd","resolution":{"observed_at":"2026-08-01T02:21:20.304733Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2311.16452","last_updated":"2023-11-28T03:16:12Z","snapshot_observed_at":"2026-08-07T08:26:36.845011Z","submitted_at":"2023-11-28T03:16:12Z","title":"Can Generalist Foundation Models Outcompete Special-Purpose Tuning? Case Study in Medicine","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2311.16452","snapshot_observed_at":"2026-08-01T02:21:20.359573Z","title":"arXiv preprint arXiv:2311.16452 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.25485","last_updated":"2026-07-28T09:24:04Z","snapshot_observed_at":"2026-08-08T05:57:13.194969Z","submitted_at":"2026-07-28T09:24:04Z","title":"PatientAgentBench: A Benchmark Framework for Evaluating Patient-Facing Health AI Agents","version":1},"reference_index":32,"source":"arxiv_source","source_observed_at":"2026-08-01T02:21:20.359573Z"},"links":{"cited_paper":"/paper/2311.16452","citing_paper":"/paper/2607.25485"},"observation_digest":"sha256:93259e28ab4273896755cb2afc87f54b19c0ef2de56d7ed360aafc17b0893879","observation_id":"39c08e43-e7f2-4c98-bf2b-6245d031a19a","resolution":{"observed_at":"2026-08-01T02:21:20.359573Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T02:21:20.483768Z","title":"Nature Medicine , volume=","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.25485","last_updated":"2026-07-28T09:24:04Z","snapshot_observed_at":"2026-08-08T05:57:13.194969Z","submitted_at":"2026-07-28T09:24:04Z","title":"PatientAgentBench: A Benchmark Framework for Evaluating Patient-Facing Health AI Agents","version":1},"reference_index":33,"source":"arxiv_source","source_observed_at":"2026-08-01T02:21:20.483768Z"},"links":{"citing_paper":"/paper/2607.25485"},"observation_digest":"sha256:d83ac89f95dd902ca9c7022b0265a4e5f1a31d74c3a21adf0c0eb3052562a669","observation_id":"340f490a-9557-44c3-9e62-c9be6692e907","resolution":{"observed_at":"2026-08-01T02:21:20.483768Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T02:21:20.580478Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.25485","last_updated":"2026-07-28T09:24:04Z","snapshot_observed_at":"2026-08-08T05:57:13.194969Z","submitted_at":"2026-07-28T09:24:04Z","title":"PatientAgentBench: A Benchmark Framework for Evaluating Patient-Facing Health AI Agents","version":1},"reference_index":34,"source":"arxiv_source","source_observed_at":"2026-08-01T02:21:20.580478Z"},"links":{"citing_paper":"/paper/2607.25485"},"observation_digest":"sha256:6698b2c2a6f9d620638706a28c8b93a0066a9aab603d88c2d3532c95efc94a08","observation_id":"2774a0b5-9ace-474d-b3db-4890fad0a887","resolution":{"observed_at":"2026-08-01T02:21:20.580478Z","resolver_source":null,"status":"parse_uncertain"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T02:21:20.689928Z","title":"2025 , url=","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.25485","last_updated":"2026-07-28T09:24:04Z","snapshot_observed_at":"2026-08-08T05:57:13.194969Z","submitted_at":"2026-07-28T09:24:04Z","title":"PatientAgentBench: A Benchmark Framework for Evaluating Patient-Facing Health AI Agents","version":1},"reference_index":35,"source":"arxiv_source","source_observed_at":"2026-08-01T02:21:20.689928Z"},"links":{"citing_paper":"/paper/2607.25485"},"observation_digest":"sha256:1f17fdac8f200f45bb99663e995e9080e9bf87c9e8d4c727a3641ebf05f8cc9a","observation_id":"83821be7-b68c-4cb1-90d5-3469c448df4f","resolution":{"observed_at":"2026-08-01T02:21:20.689928Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T02:21:20.834219Z","title":"2024 , url=","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.25485","last_updated":"2026-07-28T09:24:04Z","snapshot_observed_at":"2026-08-08T05:57:13.194969Z","submitted_at":"2026-07-28T09:24:04Z","title":"PatientAgentBench: A Benchmark Framework for Evaluating Patient-Facing Health AI Agents","version":1},"reference_index":36,"source":"arxiv_source","source_observed_at":"2026-08-01T02:21:20.834219Z"},"links":{"citing_paper":"/paper/2607.25485"},"observation_digest":"sha256:48fd9b27c6a651998b30d53839db260ff2b774838613d05e41c4d58e7bd29bf9","observation_id":"40530c6b-34a6-449a-a484-d44c8c753e4d","resolution":{"observed_at":"2026-08-01T02:21:20.834219Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T02:21:20.895142Z","title":"2025 , eprint=","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.25485","last_updated":"2026-07-28T09:24:04Z","snapshot_observed_at":"2026-08-08T05:57:13.194969Z","submitted_at":"2026-07-28T09:24:04Z","title":"PatientAgentBench: A Benchmark Framework for Evaluating Patient-Facing Health AI Agents","version":1},"reference_index":37,"source":"arxiv_source","source_observed_at":"2026-08-01T02:21:20.895142Z"},"links":{"citing_paper":"/paper/2607.25485"},"observation_digest":"sha256:2187e57775ea802768a7289047cc3ae4120f0b58685c2a192a81b40d42d731d6","observation_id":"19f2360d-aafb-4665-90e9-21aab131394d","resolution":{"observed_at":"2026-08-01T02:21:20.895142Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T02:21:20.974125Z","title":"Preference Leakage: A Contamination Problem in","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.25485","last_updated":"2026-07-28T09:24:04Z","snapshot_observed_at":"2026-08-08T05:57:13.194969Z","submitted_at":"2026-07-28T09:24:04Z","title":"PatientAgentBench: A Benchmark Framework for Evaluating Patient-Facing Health AI Agents","version":1},"reference_index":38,"source":"arxiv_source","source_observed_at":"2026-08-01T02:21:20.974125Z"},"links":{"citing_paper":"/paper/2607.25485"},"observation_digest":"sha256:1a205b5c736dd47bf55425f1ff2effb9502d5ee393c5af2183fda0930ced4a1e","observation_id":"06bd87c1-47d3-407d-888b-4f128e16389a","resolution":{"observed_at":"2026-08-01T02:21:20.974125Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.21819","last_updated":"2025-06-21T08:39:06Z","snapshot_observed_at":"2026-08-04T18:30:37.623897Z","submitted_at":"2024-10-29T07:42:18Z","title":"Self-Preference Bias in LLM-as-a-Judge","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.21819","snapshot_observed_at":"2026-08-01T02:21:21.070711Z","title":"Self-Preference Bias in","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.25485","last_updated":"2026-07-28T09:24:04Z","snapshot_observed_at":"2026-08-08T05:57:13.194969Z","submitted_at":"2026-07-28T09:24:04Z","title":"PatientAgentBench: A Benchmark Framework for Evaluating Patient-Facing Health AI Agents","version":1},"reference_index":39,"source":"arxiv_source","source_observed_at":"2026-08-01T02:21:21.070711Z"},"links":{"cited_paper":"/paper/2410.21819","citing_paper":"/paper/2607.25485"},"observation_digest":"sha256:2ad3d3b25d96f337f075e831fe5d8638b3e7f145207b17e4b1b4d1b524a799be","observation_id":"0658af29-991a-41e1-a698-6f18bbadb162","resolution":{"observed_at":"2026-08-01T02:21:21.070711Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2404.13076","last_updated":"2024-04-15T16:49:59Z","snapshot_observed_at":"2026-07-06T18:02:53.240463Z","submitted_at":"2024-04-15T16:49:59Z","title":"LLM Evaluators Recognize and Favor Their Own Generations","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.13076","snapshot_observed_at":"2026-08-01T02:21:21.118082Z","title":"and Feng, Shi , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.25485","last_updated":"2026-07-28T09:24:04Z","snapshot_observed_at":"2026-08-08T05:57:13.194969Z","submitted_at":"2026-07-28T09:24:04Z","title":"PatientAgentBench: A Benchmark Framework for Evaluating Patient-Facing Health AI Agents","version":1},"reference_index":40,"source":"arxiv_source","source_observed_at":"2026-08-01T02:21:21.118082Z"},"links":{"cited_paper":"/paper/2404.13076","citing_paper":"/paper/2607.25485"},"observation_digest":"sha256:27917d8265a0429b6d109cf5b737dc774eeb18642b085c4e667ab8638fbecf2b","observation_id":"92d99b06-3f87-4c21-a904-a0c9eaa4440c","resolution":{"observed_at":"2026-08-01T02:21:21.118082Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T02:21:21.166050Z","title":"International Conference on Learning Representations (ICLR) , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.25485","last_updated":"2026-07-28T09:24:04Z","snapshot_observed_at":"2026-08-08T05:57:13.194969Z","submitted_at":"2026-07-28T09:24:04Z","title":"PatientAgentBench: A Benchmark Framework for Evaluating Patient-Facing Health AI Agents","version":1},"reference_index":41,"source":"arxiv_source","source_observed_at":"2026-08-01T02:21:21.166050Z"},"links":{"citing_paper":"/paper/2607.25485"},"observation_digest":"sha256:4b99c2a0da95ae68e95d9df21e093831d47602d0be524aba92f47df01d85e0b6","observation_id":"8b3fba1c-eb8e-4ca3-b266-5d23955820f0","resolution":{"observed_at":"2026-08-01T02:21:21.166050Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2409.07314","last_updated":"2026-07-28T17:58:21Z","snapshot_observed_at":"2026-08-05T16:41:56.624766Z","submitted_at":"2024-09-11T14:44:51Z","title":"MEDIC: Comprehensive Evaluation of Leading Indicators for LLM Safety and Utility in Clinical Applications","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2409.07314","snapshot_observed_at":"2026-08-01T02:21:21.301494Z","title":"arXiv preprint arXiv:2409.07314 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.25485","last_updated":"2026-07-28T09:24:04Z","snapshot_observed_at":"2026-08-08T05:57:13.194969Z","submitted_at":"2026-07-28T09:24:04Z","title":"PatientAgentBench: A Benchmark Framework for Evaluating Patient-Facing Health AI Agents","version":1},"reference_index":42,"source":"arxiv_source","source_observed_at":"2026-08-01T02:21:21.301494Z"},"links":{"cited_paper":"/paper/2409.07314","citing_paper":"/paper/2607.25485"},"observation_digest":"sha256:e4f2ea2c84497173f1e956bfe99833f2f80574b33f55e954fb4d0051d5d1155b","observation_id":"913a0366-970a-461d-a17a-14865e2d0ea9","resolution":{"observed_at":"2026-08-01T02:21:21.301494Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T02:21:21.360242Z","title":"Scientific Data , volume=","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2607.25485","last_updated":"2026-07-28T09:24:04Z","snapshot_observed_at":"2026-08-08T05:57:13.194969Z","submitted_at":"2026-07-28T09:24:04Z","title":"PatientAgentBench: A Benchmark Framework for Evaluating Patient-Facing Health AI Agents","version":1},"reference_index":43,"source":"arxiv_source","source_observed_at":"2026-08-01T02:21:21.360242Z"},"links":{"citing_paper":"/paper/2607.25485"},"observation_digest":"sha256:8ffd944770f5eb6bd3879c36c584788c95205d2e39c12930076e591a501cf190","observation_id":"57ce7a47-62f4-4c2c-87f6-463013feeb28","resolution":{"observed_at":"2026-08-01T02:21:21.360242Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T02:21:21.379807Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.25485","last_updated":"2026-07-28T09:24:04Z","snapshot_observed_at":"2026-08-08T05:57:13.194969Z","submitted_at":"2026-07-28T09:24:04Z","title":"PatientAgentBench: A Benchmark Framework for Evaluating Patient-Facing Health AI Agents","version":1},"reference_index":44,"source":"arxiv_source","source_observed_at":"2026-08-01T02:21:21.379807Z"},"links":{"citing_paper":"/paper/2607.25485"},"observation_digest":"sha256:c6346652a1e1044d968094b3ac85c4788f8fca8baf57a9d67ef03390e45dabaf","observation_id":"e726d091-3c72-4722-9af6-8bb128dc51e4","resolution":{"observed_at":"2026-08-01T02:21:21.379807Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2502.14860","last_updated":"2025-08-11T03:23:40Z","snapshot_observed_at":"2026-08-08T09:54:44.787669Z","submitted_at":"2025-02-20T18:59:31Z","title":"ALFA: Aligning LLMs to Ask Good Questions A Case Study in Clinical Reasoning","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2502.14860","snapshot_observed_at":"2026-08-01T02:21:21.414682Z","title":"Thomas and Jessica M","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.25485","last_updated":"2026-07-28T09:24:04Z","snapshot_observed_at":"2026-08-08T05:57:13.194969Z","submitted_at":"2026-07-28T09:24:04Z","title":"PatientAgentBench: A Benchmark Framework for Evaluating Patient-Facing Health AI Agents","version":1},"reference_index":45,"source":"arxiv_source","source_observed_at":"2026-08-01T02:21:21.414682Z"},"links":{"cited_paper":"/paper/2502.14860","citing_paper":"/paper/2607.25485"},"observation_digest":"sha256:06c7e35401bf782790f8adb9746f43799af1bafed89035235ccd6529a62b0d05","observation_id":"919727a7-8220-416f-bfff-9ce2953554a0","resolution":{"observed_at":"2026-08-01T02:21:21.414682Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T02:21:21.452299Z","title":"Applied Sciences , volume=","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2607.25485","last_updated":"2026-07-28T09:24:04Z","snapshot_observed_at":"2026-08-08T05:57:13.194969Z","submitted_at":"2026-07-28T09:24:04Z","title":"PatientAgentBench: A Benchmark Framework for Evaluating Patient-Facing Health AI Agents","version":1},"reference_index":46,"source":"arxiv_source","source_observed_at":"2026-08-01T02:21:21.452299Z"},"links":{"citing_paper":"/paper/2607.25485"},"observation_digest":"sha256:9c833f96df6b46cee20db60c96f86b2e430254e16030594a68fe2d3f2ba214cf","observation_id":"1750fc42-26ec-4ad0-9c54-366008523316","resolution":{"observed_at":"2026-08-01T02:21:21.452299Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T02:21:21.486668Z","title":"International Conference on Learning Representations (ICLR) , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.25485","last_updated":"2026-07-28T09:24:04Z","snapshot_observed_at":"2026-08-08T05:57:13.194969Z","submitted_at":"2026-07-28T09:24:04Z","title":"PatientAgentBench: A Benchmark Framework for Evaluating Patient-Facing Health AI Agents","version":1},"reference_index":47,"source":"arxiv_source","source_observed_at":"2026-08-01T02:21:21.486668Z"},"links":{"citing_paper":"/paper/2607.25485"},"observation_digest":"sha256:17f3efcd929181d11efd1584829085563af3824949cda81320eedaf98fff8153","observation_id":"1c1951a3-9aee-448d-8aa8-70628b357b14","resolution":{"observed_at":"2026-08-01T02:21:21.486668Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T02:21:21.516041Z","title":"International Conference on Learning Representations (ICLR) , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.25485","last_updated":"2026-07-28T09:24:04Z","snapshot_observed_at":"2026-08-08T05:57:13.194969Z","submitted_at":"2026-07-28T09:24:04Z","title":"PatientAgentBench: A Benchmark Framework for Evaluating Patient-Facing Health AI Agents","version":1},"reference_index":48,"source":"arxiv_source","source_observed_at":"2026-08-01T02:21:21.516041Z"},"links":{"citing_paper":"/paper/2607.25485"},"observation_digest":"sha256:6e273e11543cd84bbd0401138eda473f8e0b7252d2b020d7c23976573b973671","observation_id":"9e80aeb1-43f5-4fac-95fe-d408bc533dbe","resolution":{"observed_at":"2026-08-01T02:21:21.516041Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T02:21:21.563135Z","title":"PARADISE : a framework for evaluating spoken dialogue agents","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.25485","last_updated":"2026-07-28T09:24:04Z","snapshot_observed_at":"2026-08-08T05:57:13.194969Z","submitted_at":"2026-07-28T09:24:04Z","title":"PatientAgentBench: A Benchmark Framework for Evaluating Patient-Facing Health AI Agents","version":1},"reference_index":49,"source":"arxiv_source","source_observed_at":"2026-08-01T02:21:21.563135Z"},"links":{"citing_paper":"/paper/2607.25485"},"observation_digest":"sha256:e350dc64292f381b40c73a0f39e3e2906f9b1afc5ff041617d55ff2447025122","observation_id":"4355c556-d7ab-47f6-b90c-abe9f23a7ecd","resolution":{"observed_at":"2026-08-01T02:21:21.563135Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T02:21:21.612110Z","title":"Towards an automatic Turing test: Learning to evaluate dialogue responses","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.25485","last_updated":"2026-07-28T09:24:04Z","snapshot_observed_at":"2026-08-08T05:57:13.194969Z","submitted_at":"2026-07-28T09:24:04Z","title":"PatientAgentBench: A Benchmark Framework for Evaluating Patient-Facing Health AI Agents","version":1},"reference_index":50,"source":"arxiv_source","source_observed_at":"2026-08-01T02:21:21.612110Z"},"links":{"citing_paper":"/paper/2607.25485"},"observation_digest":"sha256:f544670a88d6c687dfbd92bb5af4f071f6ccfc41fc57c1b41ef2640843b96d23","observation_id":"4bedea21-e4f8-4cfd-b789-0f3487d0d447","resolution":{"observed_at":"2026-08-01T02:21:21.612110Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2501.18362","last_updated":"2025-06-06T13:00:07Z","snapshot_observed_at":"2026-07-06T20:28:24.203633Z","submitted_at":"2025-01-30T14:07:56Z","title":"MedXpertQA: Benchmarking Expert-Level Medical Reasoning and Understanding","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2501.18362","snapshot_observed_at":"2026-08-01T02:21:21.671396Z","title":"Proceedings of the 42nd International Conference on Machine Learning (ICML) , year =","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.25485","last_updated":"2026-07-28T09:24:04Z","snapshot_observed_at":"2026-08-08T05:57:13.194969Z","submitted_at":"2026-07-28T09:24:04Z","title":"PatientAgentBench: A Benchmark Framework for Evaluating Patient-Facing Health AI Agents","version":1},"reference_index":51,"source":"arxiv_source","source_observed_at":"2026-08-01T02:21:21.671396Z"},"links":{"cited_paper":"/paper/2501.18362","citing_paper":"/paper/2607.25485"},"observation_digest":"sha256:8ef24ea2b337b4e5993c2d2e02b727b8514404bfa8eeeaa92b6b1db396ca43e7","observation_id":"81cfd0c9-d0ce-4fb6-a6a4-312c336c1c78","resolution":{"observed_at":"2026-08-01T02:21:21.671396Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T02:21:21.720085Z","title":"Proceedings of the 31st International Conference on Computational Linguistics (COLING) , pages =","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.25485","last_updated":"2026-07-28T09:24:04Z","snapshot_observed_at":"2026-08-08T05:57:13.194969Z","submitted_at":"2026-07-28T09:24:04Z","title":"PatientAgentBench: A Benchmark Framework for Evaluating Patient-Facing Health AI Agents","version":1},"reference_index":52,"source":"arxiv_source","source_observed_at":"2026-08-01T02:21:21.720085Z"},"links":{"citing_paper":"/paper/2607.25485"},"observation_digest":"sha256:1fa93b5e999788af189c99411148b2a92e1eaffc80688208ab0a0688f51ee059","observation_id":"2fc661a9-25c8-48d8-a067-79c2490aee2c","resolution":{"observed_at":"2026-08-01T02:21:21.720085Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T02:21:21.756090Z","title":"arXiv preprint arXiv:2601.03023 , year =","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.25485","last_updated":"2026-07-28T09:24:04Z","snapshot_observed_at":"2026-08-08T05:57:13.194969Z","submitted_at":"2026-07-28T09:24:04Z","title":"PatientAgentBench: A Benchmark Framework for Evaluating Patient-Facing Health AI Agents","version":1},"reference_index":53,"source":"arxiv_source","source_observed_at":"2026-08-01T02:21:21.756090Z"},"links":{"citing_paper":"/paper/2607.25485"},"observation_digest":"sha256:22804ef082bab351e9ca3f8e086f5331a1735550b8904e8ed57b8a572e617e8c","observation_id":"889aafdc-abcd-4541-b19f-22104f8d90e2","resolution":{"observed_at":"2026-08-01T02:21:21.756090Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T02:21:21.800471Z","title":"and Geng, Gloria and Park, Danny and Zou, James and Ng, Andrew Y","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.25485","last_updated":"2026-07-28T09:24:04Z","snapshot_observed_at":"2026-08-08T05:57:13.194969Z","submitted_at":"2026-07-28T09:24:04Z","title":"PatientAgentBench: A Benchmark Framework for Evaluating Patient-Facing Health AI Agents","version":1},"reference_index":54,"source":"arxiv_source","source_observed_at":"2026-08-01T02:21:21.800471Z"},"links":{"citing_paper":"/paper/2607.25485"},"observation_digest":"sha256:8c608ea1f6e5452fbc464cd66f1ddd99c87b38f2a82bf03de8cc3acbe0303a2b","observation_id":"358a967d-b42d-4908-b5ce-b193a960e88f","resolution":{"observed_at":"2026-08-01T02:21:21.800471Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T02:21:21.840303Z","title":"Advances in Neural Information Processing Systems (NeurIPS), Datasets and Benchmarks Track , volume =","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.25485","last_updated":"2026-07-28T09:24:04Z","snapshot_observed_at":"2026-08-08T05:57:13.194969Z","submitted_at":"2026-07-28T09:24:04Z","title":"PatientAgentBench: A Benchmark Framework for Evaluating Patient-Facing Health AI Agents","version":1},"reference_index":55,"source":"arxiv_source","source_observed_at":"2026-08-01T02:21:21.840303Z"},"links":{"citing_paper":"/paper/2607.25485"},"observation_digest":"sha256:1b56eb227ed397deff86d0750777947be4710a9a1e2736706082eeb3d4995593","observation_id":"192c1a86-9ffc-4b4a-a1d5-ce80e0710139","resolution":{"observed_at":"2026-08-01T02:21:21.840303Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T02:21:21.893864Z","title":"and He, Junjun and Qiao, Yu , booktitle =","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.25485","last_updated":"2026-07-28T09:24:04Z","snapshot_observed_at":"2026-08-08T05:57:13.194969Z","submitted_at":"2026-07-28T09:24:04Z","title":"PatientAgentBench: A Benchmark Framework for Evaluating Patient-Facing Health AI Agents","version":1},"reference_index":56,"source":"arxiv_source","source_observed_at":"2026-08-01T02:21:21.893864Z"},"links":{"citing_paper":"/paper/2607.25485"},"observation_digest":"sha256:aaff815b2489f83e5e9a2cf3c5f0efa27ef9e766c389c2dc8990fba3f8b4e306","observation_id":"7f1af8b4-ae71-4e87-864a-c6bfca68d5d0","resolution":{"observed_at":"2026-08-01T02:21:21.893864Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T02:21:21.934658Z","title":"ClinicalBench: Can","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.25485","last_updated":"2026-07-28T09:24:04Z","snapshot_observed_at":"2026-08-08T05:57:13.194969Z","submitted_at":"2026-07-28T09:24:04Z","title":"PatientAgentBench: A Benchmark Framework for Evaluating Patient-Facing Health AI Agents","version":1},"reference_index":57,"source":"arxiv_source","source_observed_at":"2026-08-01T02:21:21.934658Z"},"links":{"citing_paper":"/paper/2607.25485"},"observation_digest":"sha256:acfa8c30ef3600416b1552c8eada761475affba8b6049522da2ed24b6adb2bf5","observation_id":"a30e99a9-1327-476c-b4bc-e0e6128631df","resolution":{"observed_at":"2026-08-01T02:21:21.934658Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T02:21:21.982167Z","title":"Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing (EMNLP) , pages =","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.25485","last_updated":"2026-07-28T09:24:04Z","snapshot_observed_at":"2026-08-08T05:57:13.194969Z","submitted_at":"2026-07-28T09:24:04Z","title":"PatientAgentBench: A Benchmark Framework for Evaluating Patient-Facing Health AI Agents","version":1},"reference_index":58,"source":"arxiv_source","source_observed_at":"2026-08-01T02:21:21.982167Z"},"links":{"citing_paper":"/paper/2607.25485"},"observation_digest":"sha256:5c4ccac42f2bfbc61b416893a18995af6ca63e44221217cf5a2a8f6e5a943d8f","observation_id":"d88614ee-8082-4a69-9e1d-aa4c9220d53a","resolution":{"observed_at":"2026-08-01T02:21:21.982167Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2406.12045","last_updated":"2024-06-17T19:33:08Z","snapshot_observed_at":"2026-08-08T11:30:35.242922Z","submitted_at":"2024-06-17T19:33:08Z","title":"$\\tau$-bench: A Benchmark for Tool-Agent-User Interaction in Real-World Domains","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2406.12045","snapshot_observed_at":"2026-08-01T02:21:22.026928Z","title":"International Conference on Learning Representations (ICLR) , year =","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.25485","last_updated":"2026-07-28T09:24:04Z","snapshot_observed_at":"2026-08-08T05:57:13.194969Z","submitted_at":"2026-07-28T09:24:04Z","title":"PatientAgentBench: A Benchmark Framework for Evaluating Patient-Facing Health AI Agents","version":1},"reference_index":59,"source":"arxiv_source","source_observed_at":"2026-08-01T02:21:22.026928Z"},"links":{"cited_paper":"/paper/2406.12045","citing_paper":"/paper/2607.25485"},"observation_digest":"sha256:c346ea7027d5cfa63add07b473e9e9e1288d65dae272bb87cd7e6c3f025e5241","observation_id":"d3b2b9ca-5269-43b2-8cfa-aaefcdd9ef89","resolution":{"observed_at":"2026-08-01T02:21:22.026928Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2404.18796","last_updated":"2024-05-01T15:37:11Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-04-29T15:33:23Z","title":"Replacing Judges with Juries: Evaluating LLM Generations with a Panel of Diverse Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.18796","snapshot_observed_at":"2026-08-01T02:21:22.083147Z","title":"Replacing Judges with Juries: Evaluating","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.25485","last_updated":"2026-07-28T09:24:04Z","snapshot_observed_at":"2026-08-08T05:57:13.194969Z","submitted_at":"2026-07-28T09:24:04Z","title":"PatientAgentBench: A Benchmark Framework for Evaluating Patient-Facing Health AI Agents","version":1},"reference_index":60,"source":"arxiv_source","source_observed_at":"2026-08-01T02:21:22.083147Z"},"links":{"cited_paper":"/paper/2404.18796","citing_paper":"/paper/2607.25485"},"observation_digest":"sha256:3387da57543fcf34fb4aa1b6445daa3372fbe213c4e46aca430abb899009249d","observation_id":"68867839-324e-42d0-8aba-4a4586818b24","resolution":{"observed_at":"2026-08-01T02:21:22.083147Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T02:21:22.136648Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.25485","last_updated":"2026-07-28T09:24:04Z","snapshot_observed_at":"2026-08-08T05:57:13.194969Z","submitted_at":"2026-07-28T09:24:04Z","title":"PatientAgentBench: A Benchmark Framework for Evaluating Patient-Facing Health AI Agents","version":1},"reference_index":61,"source":"arxiv_source","source_observed_at":"2026-08-01T02:21:22.136648Z"},"links":{"citing_paper":"/paper/2607.25485"},"observation_digest":"sha256:5e9dc0994f2dfeb04b3e206e08fdf491a23f05cf2816b03682cc8a325cc6e3ab","observation_id":"8fa8e008-fdcf-4db9-8819-51b6ca835571","resolution":{"observed_at":"2026-08-01T02:21:22.136648Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T02:21:22.234690Z","title":"and Mao, Huanzhi and Yan, Fanjia and Ji, Charlie Cheng-Jie and Suresh, Vishnu and Stoica, Ion and Gonzalez, Joseph E","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.25485","last_updated":"2026-07-28T09:24:04Z","snapshot_observed_at":"2026-08-08T05:57:13.194969Z","submitted_at":"2026-07-28T09:24:04Z","title":"PatientAgentBench: A Benchmark Framework for Evaluating Patient-Facing Health AI Agents","version":1},"reference_index":62,"source":"arxiv_source","source_observed_at":"2026-08-01T02:21:22.234690Z"},"links":{"citing_paper":"/paper/2607.25485"},"observation_digest":"sha256:9be8be05a2b5120661e8079ffe8cdbe43ebc663ad86886c483a0ef7b67fb9db8","observation_id":"63aec43f-d4ba-4da9-bc64-31b744f43b7d","resolution":{"observed_at":"2026-08-01T02:21:22.234690Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T02:21:22.258825Z","title":"Journal of Medical Internet Research , volume =","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2607.25485","last_updated":"2026-07-28T09:24:04Z","snapshot_observed_at":"2026-08-08T05:57:13.194969Z","submitted_at":"2026-07-28T09:24:04Z","title":"PatientAgentBench: A Benchmark Framework for Evaluating Patient-Facing Health AI Agents","version":1},"reference_index":63,"source":"arxiv_source","source_observed_at":"2026-08-01T02:21:22.258825Z"},"links":{"citing_paper":"/paper/2607.25485"},"observation_digest":"sha256:6e70d1e5707d31bf8f22881f8de1af24900d5f5075289955879378c41036781e","observation_id":"de1fbce5-bb35-481b-bb7e-5a7a6ded9627","resolution":{"observed_at":"2026-08-01T02:21:22.258825Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T02:21:22.290120Z","title":"Journal of Medical Internet Research , volume =","venue":null,"work_id":null,"year":2020},"citing_paper":{"arxiv_id":"2607.25485","last_updated":"2026-07-28T09:24:04Z","snapshot_observed_at":"2026-08-08T05:57:13.194969Z","submitted_at":"2026-07-28T09:24:04Z","title":"PatientAgentBench: A Benchmark Framework for Evaluating Patient-Facing Health AI Agents","version":1},"reference_index":64,"source":"arxiv_source","source_observed_at":"2026-08-01T02:21:22.290120Z"},"links":{"citing_paper":"/paper/2607.25485"},"observation_digest":"sha256:c0b63e6fe249cb4bae9b10323496ff7ee87eae4ce47c321bff8ceeb431a31e1a","observation_id":"5c80304c-4a3e-4169-b328-da3805979977","resolution":{"observed_at":"2026-08-01T02:21:22.290120Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T02:21:22.330553Z","title":"Journal of the American Medical Informatics Association , volume =","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2607.25485","last_updated":"2026-07-28T09:24:04Z","snapshot_observed_at":"2026-08-08T05:57:13.194969Z","submitted_at":"2026-07-28T09:24:04Z","title":"PatientAgentBench: A Benchmark Framework for Evaluating Patient-Facing Health AI Agents","version":1},"reference_index":65,"source":"arxiv_source","source_observed_at":"2026-08-01T02:21:22.330553Z"},"links":{"citing_paper":"/paper/2607.25485"},"observation_digest":"sha256:95209600888c5836c447382791679c4c4429aebb7fccb0c4a6f771f639367697","observation_id":"5467353b-d1c7-487a-9086-04c91a2817b6","resolution":{"observed_at":"2026-08-01T02:21:22.330553Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T02:21:22.381143Z","title":"Journal of Medical Internet Research , volume =","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2607.25485","last_updated":"2026-07-28T09:24:04Z","snapshot_observed_at":"2026-08-08T05:57:13.194969Z","submitted_at":"2026-07-28T09:24:04Z","title":"PatientAgentBench: A Benchmark Framework for Evaluating Patient-Facing Health AI Agents","version":1},"reference_index":66,"source":"arxiv_source","source_observed_at":"2026-08-01T02:21:22.381143Z"},"links":{"citing_paper":"/paper/2607.25485"},"observation_digest":"sha256:41e1e22f90faf9b2728237bd4affc32a1ada961c9aa1c600dbb1d238a25f91f9","observation_id":"3956f1df-4c78-4a65-bce7-0251293db865","resolution":{"observed_at":"2026-08-01T02:21:22.381143Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T02:21:22.413787Z","title":"npj Digital Medicine , volume =","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2607.25485","last_updated":"2026-07-28T09:24:04Z","snapshot_observed_at":"2026-08-08T05:57:13.194969Z","submitted_at":"2026-07-28T09:24:04Z","title":"PatientAgentBench: A Benchmark Framework for Evaluating Patient-Facing Health AI Agents","version":1},"reference_index":67,"source":"arxiv_source","source_observed_at":"2026-08-01T02:21:22.413787Z"},"links":{"citing_paper":"/paper/2607.25485"},"observation_digest":"sha256:b8f0cecd5dec7f722c477b035eff2fbc6446310926ed25ba35072775492439a1","observation_id":"99e3c458-7e76-4afc-ba8c-49657f8a1759","resolution":{"observed_at":"2026-08-01T02:21:22.413787Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T02:21:22.442579Z","title":"Journal of Medical Internet Research , volume =","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.25485","last_updated":"2026-07-28T09:24:04Z","snapshot_observed_at":"2026-08-08T05:57:13.194969Z","submitted_at":"2026-07-28T09:24:04Z","title":"PatientAgentBench: A Benchmark Framework for Evaluating Patient-Facing Health AI Agents","version":1},"reference_index":68,"source":"arxiv_source","source_observed_at":"2026-08-01T02:21:22.442579Z"},"links":{"citing_paper":"/paper/2607.25485"},"observation_digest":"sha256:519fb0955a50a35d4c7049eb429362fc07d8888f7310910e2ba9e5bfd1601596","observation_id":"621d281b-c99d-4e1b-a222-189c274ff6f8","resolution":{"observed_at":"2026-08-01T02:21:22.442579Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T02:21:22.475559Z","title":"PLOS ONE , volume =","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2607.25485","last_updated":"2026-07-28T09:24:04Z","snapshot_observed_at":"2026-08-08T05:57:13.194969Z","submitted_at":"2026-07-28T09:24:04Z","title":"PatientAgentBench: A Benchmark Framework for Evaluating Patient-Facing Health AI Agents","version":1},"reference_index":69,"source":"arxiv_source","source_observed_at":"2026-08-01T02:21:22.475559Z"},"links":{"citing_paper":"/paper/2607.25485"},"observation_digest":"sha256:cb9cfa0867e16854fe4efb3eb46f2946061e5dc3a10e03c3457fb89ad9abca26","observation_id":"2e8d33b3-5744-4a1c-b2d5-aa4b5cd71ac2","resolution":{"observed_at":"2026-08-01T02:21:22.475559Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T02:21:22.498424Z","title":"BMJ Open , volume =","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2607.25485","last_updated":"2026-07-28T09:24:04Z","snapshot_observed_at":"2026-08-08T05:57:13.194969Z","submitted_at":"2026-07-28T09:24:04Z","title":"PatientAgentBench: A Benchmark Framework for Evaluating Patient-Facing Health AI Agents","version":1},"reference_index":70,"source":"arxiv_source","source_observed_at":"2026-08-01T02:21:22.498424Z"},"links":{"citing_paper":"/paper/2607.25485"},"observation_digest":"sha256:ba2b7410594e4aea1820477e62014852f0b225a8b9f2705bd3160cd645b1b764","observation_id":"daf8417d-68ec-4074-83f5-fa72605b7898","resolution":{"observed_at":"2026-08-01T02:21:22.498424Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2310.19736","last_updated":"2023-11-25T17:35:12Z","snapshot_observed_at":"2026-07-06T16:40:35.590974Z","submitted_at":"2023-10-30T17:00:52Z","title":"Evaluating Large Language Models: A Comprehensive Survey","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.19736","snapshot_observed_at":"2026-08-01T02:21:22.521574Z","title":"arXiv preprint arXiv:2310.19736 , year =","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.25485","last_updated":"2026-07-28T09:24:04Z","snapshot_observed_at":"2026-08-08T05:57:13.194969Z","submitted_at":"2026-07-28T09:24:04Z","title":"PatientAgentBench: A Benchmark Framework for Evaluating Patient-Facing Health AI Agents","version":1},"reference_index":71,"source":"arxiv_source","source_observed_at":"2026-08-01T02:21:22.521574Z"},"links":{"cited_paper":"/paper/2310.19736","citing_paper":"/paper/2607.25485"},"observation_digest":"sha256:52a76e58e27d2370863aa1dad0b71190551f04ec38fa647364da758419017200","observation_id":"f3c6c9d6-cbec-4b73-bb34-fc4e24f7b3d7","resolution":{"observed_at":"2026-08-01T02:21:22.521574Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T02:21:22.554244Z","title":"Nature , volume =","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.25485","last_updated":"2026-07-28T09:24:04Z","snapshot_observed_at":"2026-08-08T05:57:13.194969Z","submitted_at":"2026-07-28T09:24:04Z","title":"PatientAgentBench: A Benchmark Framework for Evaluating Patient-Facing Health AI Agents","version":1},"reference_index":72,"source":"arxiv_source","source_observed_at":"2026-08-01T02:21:22.554244Z"},"links":{"citing_paper":"/paper/2607.25485"},"observation_digest":"sha256:3938df52849a20bfe54aa5dfc0e09bbadda3d8fcbd3da34a87e41099ce123647","observation_id":"1d8f8230-c9c7-4dc7-9701-d771716a0fb8","resolution":{"observed_at":"2026-08-01T02:21:22.554244Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T02:21:22.597328Z","title":"Nature Medicine , volume =","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.25485","last_updated":"2026-07-28T09:24:04Z","snapshot_observed_at":"2026-08-08T05:57:13.194969Z","submitted_at":"2026-07-28T09:24:04Z","title":"PatientAgentBench: A Benchmark Framework for Evaluating Patient-Facing Health AI Agents","version":1},"reference_index":73,"source":"arxiv_source","source_observed_at":"2026-08-01T02:21:22.597328Z"},"links":{"citing_paper":"/paper/2607.25485"},"observation_digest":"sha256:191c33be8cfd4f2cb0c3d73c032418be7990f535f29938d4fc19cdbd89b94941","observation_id":"3aaf1d19-7dfc-4022-a09f-92b15b08ef08","resolution":{"observed_at":"2026-08-01T02:21:22.597328Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2505.08775","last_updated":"2025-05-13T17:53:59Z","snapshot_observed_at":"2026-07-06T21:23:23.760393Z","submitted_at":"2025-05-13T17:53:59Z","title":"HealthBench: Evaluating Large Language Models Towards Improved Human Health","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2505.08775","snapshot_observed_at":"2026-08-01T02:21:22.633720Z","title":"arXiv preprint arXiv:2505.08775 , year =","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.25485","last_updated":"2026-07-28T09:24:04Z","snapshot_observed_at":"2026-08-08T05:57:13.194969Z","submitted_at":"2026-07-28T09:24:04Z","title":"PatientAgentBench: A Benchmark Framework for Evaluating Patient-Facing Health AI Agents","version":1},"reference_index":74,"source":"arxiv_source","source_observed_at":"2026-08-01T02:21:22.633720Z"},"links":{"cited_paper":"/paper/2505.08775","citing_paper":"/paper/2607.25485"},"observation_digest":"sha256:5a9740320ce160ddb916fcc4006761724911033ccdbcc2750dff5bfb227fa82e","observation_id":"ed50d4a6-c454-4aed-8004-7289d0df48b2","resolution":{"observed_at":"2026-08-01T02:21:22.633720Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T02:21:22.662260Z","title":"Annals of Internal Medicine , volume =","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2607.25485","last_updated":"2026-07-28T09:24:04Z","snapshot_observed_at":"2026-08-08T05:57:13.194969Z","submitted_at":"2026-07-28T09:24:04Z","title":"PatientAgentBench: A Benchmark Framework for Evaluating Patient-Facing Health AI Agents","version":1},"reference_index":75,"source":"arxiv_source","source_observed_at":"2026-08-01T02:21:22.662260Z"},"links":{"citing_paper":"/paper/2607.25485"},"observation_digest":"sha256:b45acf8117ea2b29138bfb512f900f2156a0ab18f09e002eb99584da4e1d071d","observation_id":"b99d2425-4fbf-4224-b2fc-4855c7c9b477","resolution":{"observed_at":"2026-08-01T02:21:22.662260Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T02:21:22.672978Z","title":"Annals of Family Medicine , volume =","venue":null,"work_id":null,"year":2011},"citing_paper":{"arxiv_id":"2607.25485","last_updated":"2026-07-28T09:24:04Z","snapshot_observed_at":"2026-08-08T05:57:13.194969Z","submitted_at":"2026-07-28T09:24:04Z","title":"PatientAgentBench: A Benchmark Framework for Evaluating Patient-Facing Health AI Agents","version":1},"reference_index":76,"source":"arxiv_source","source_observed_at":"2026-08-01T02:21:22.672978Z"},"links":{"citing_paper":"/paper/2607.25485"},"observation_digest":"sha256:cd2a651e7a311d1517f72df98a9c92f26e646e2491ceefd71e74357214ee33ef","observation_id":"1d8974f7-43a0-4a1b-aa11-0673bffc94a4","resolution":{"observed_at":"2026-08-01T02:21:22.672978Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T02:21:22.701316Z","title":"2026 , note =","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2607.25485","last_updated":"2026-07-28T09:24:04Z","snapshot_observed_at":"2026-08-08T05:57:13.194969Z","submitted_at":"2026-07-28T09:24:04Z","title":"PatientAgentBench: A Benchmark Framework for Evaluating Patient-Facing Health AI Agents","version":1},"reference_index":77,"source":"arxiv_source","source_observed_at":"2026-08-01T02:21:22.701316Z"},"links":{"citing_paper":"/paper/2607.25485"},"observation_digest":"sha256:ba9eed067c54ac9c8464b0931a285e2381afad037f9a8fb27dc59a1187447568","observation_id":"24a98490-6834-41b2-89e2-18859d70cc3c","resolution":{"observed_at":"2026-08-01T02:21:22.701316Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T02:21:22.761287Z","title":"2025 , eprint =","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.25485","last_updated":"2026-07-28T09:24:04Z","snapshot_observed_at":"2026-08-08T05:57:13.194969Z","submitted_at":"2026-07-28T09:24:04Z","title":"PatientAgentBench: A Benchmark Framework for Evaluating Patient-Facing Health AI Agents","version":1},"reference_index":78,"source":"arxiv_source","source_observed_at":"2026-08-01T02:21:22.761287Z"},"links":{"citing_paper":"/paper/2607.25485"},"observation_digest":"sha256:118ba218a60473e82aec9e98cfdd49d53f5f123ec6e8ed33cb1601df0f6b119f","observation_id":"ffa6a04d-d682-4a41-917b-a8e4c1feecd1","resolution":{"observed_at":"2026-08-01T02:21:22.761287Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T02:21:22.796414Z","title":"arXiv preprint arXiv:2511.18491 , year =","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.25485","last_updated":"2026-07-28T09:24:04Z","snapshot_observed_at":"2026-08-08T05:57:13.194969Z","submitted_at":"2026-07-28T09:24:04Z","title":"PatientAgentBench: A Benchmark Framework for Evaluating Patient-Facing Health AI Agents","version":1},"reference_index":79,"source":"arxiv_source","source_observed_at":"2026-08-01T02:21:22.796414Z"},"links":{"citing_paper":"/paper/2607.25485"},"observation_digest":"sha256:567b45e1ad202e57d5deb003291a7847a77229818c3b29aa0b988d9f076d802e","observation_id":"a22b90e4-3f35-4165-8489-570cfa65064d","resolution":{"observed_at":"2026-08-01T02:21:22.796414Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T02:21:22.826642Z","title":"Nature , volume =","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.25485","last_updated":"2026-07-28T09:24:04Z","snapshot_observed_at":"2026-08-08T05:57:13.194969Z","submitted_at":"2026-07-28T09:24:04Z","title":"PatientAgentBench: A Benchmark Framework for Evaluating Patient-Facing Health AI Agents","version":1},"reference_index":80,"source":"arxiv_source","source_observed_at":"2026-08-01T02:21:22.826642Z"},"links":{"citing_paper":"/paper/2607.25485"},"observation_digest":"sha256:e8102261af77e7a2a2da3e4067c81260d4df7e73564c983fd0f050c6ce100e11","observation_id":"44199887-95a3-4403-b665-af61c1d84a11","resolution":{"observed_at":"2026-08-01T02:21:22.826642Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T02:21:22.871152Z","title":"Nature , volume =","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.25485","last_updated":"2026-07-28T09:24:04Z","snapshot_observed_at":"2026-08-08T05:57:13.194969Z","submitted_at":"2026-07-28T09:24:04Z","title":"PatientAgentBench: A Benchmark Framework for Evaluating Patient-Facing Health AI Agents","version":1},"reference_index":81,"source":"arxiv_source","source_observed_at":"2026-08-01T02:21:22.871152Z"},"links":{"citing_paper":"/paper/2607.25485"},"observation_digest":"sha256:70d1a42ede77a2c484426da20c859e50537d0218c9c9b133ab17e693eeecab61","observation_id":"240469f4-8160-449b-8357-651204248943","resolution":{"observed_at":"2026-08-01T02:21:22.871152Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T02:21:22.903895Z","title":"Nature Medicine , volume =","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.25485","last_updated":"2026-07-28T09:24:04Z","snapshot_observed_at":"2026-08-08T05:57:13.194969Z","submitted_at":"2026-07-28T09:24:04Z","title":"PatientAgentBench: A Benchmark Framework for Evaluating Patient-Facing Health AI Agents","version":1},"reference_index":82,"source":"arxiv_source","source_observed_at":"2026-08-01T02:21:22.903895Z"},"links":{"citing_paper":"/paper/2607.25485"},"observation_digest":"sha256:4dba0d61a15766996a4fa821d251853d1eab98499a6ee33fd6379be4f3bf6504","observation_id":"e0bde585-f68a-4e08-9288-f3a9a7e5aa17","resolution":{"observed_at":"2026-08-01T02:21:22.903895Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T02:21:22.933035Z","title":"Nature Medicine , volume =","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.25485","last_updated":"2026-07-28T09:24:04Z","snapshot_observed_at":"2026-08-08T05:57:13.194969Z","submitted_at":"2026-07-28T09:24:04Z","title":"PatientAgentBench: A Benchmark Framework for Evaluating Patient-Facing Health AI Agents","version":1},"reference_index":83,"source":"arxiv_source","source_observed_at":"2026-08-01T02:21:22.933035Z"},"links":{"citing_paper":"/paper/2607.25485"},"observation_digest":"sha256:3bb77b27789abe4b9321f56b53d450d4377d78d59b0f3e994d60f1fa686d1fac","observation_id":"cd35f801-4760-4278-a5ea-17ce71bfde78","resolution":{"observed_at":"2026-08-01T02:21:22.933035Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T02:21:22.965492Z","title":"JAMA , volume =","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.25485","last_updated":"2026-07-28T09:24:04Z","snapshot_observed_at":"2026-08-08T05:57:13.194969Z","submitted_at":"2026-07-28T09:24:04Z","title":"PatientAgentBench: A Benchmark Framework for Evaluating Patient-Facing Health AI Agents","version":1},"reference_index":84,"source":"arxiv_source","source_observed_at":"2026-08-01T02:21:22.965492Z"},"links":{"citing_paper":"/paper/2607.25485"},"observation_digest":"sha256:608025232e49ac4b87729fcddd4f6cd174fc70928a3d514e944d4f5d3b37af84","observation_id":"5c6e3de3-a465-40e3-8d67-dc441c1b39f8","resolution":{"observed_at":"2026-08-01T02:21:22.965492Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T02:21:23.002220Z","title":"npj Digital Medicine , volume =","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2607.25485","last_updated":"2026-07-28T09:24:04Z","snapshot_observed_at":"2026-08-08T05:57:13.194969Z","submitted_at":"2026-07-28T09:24:04Z","title":"PatientAgentBench: A Benchmark Framework for Evaluating Patient-Facing Health AI Agents","version":1},"reference_index":85,"source":"arxiv_source","source_observed_at":"2026-08-01T02:21:23.002220Z"},"links":{"citing_paper":"/paper/2607.25485"},"observation_digest":"sha256:30db7be889fb0ce9e846ecb52200f718f96e718783bf2d2c800096f5f6d7888d","observation_id":"aea814bd-a2cb-4763-af3d-ac003bdb41fa","resolution":{"observed_at":"2026-08-01T02:21:23.002220Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T02:21:23.045209Z","title":"JAMA Network Open , volume =","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.25485","last_updated":"2026-07-28T09:24:04Z","snapshot_observed_at":"2026-08-08T05:57:13.194969Z","submitted_at":"2026-07-28T09:24:04Z","title":"PatientAgentBench: A Benchmark Framework for Evaluating Patient-Facing Health AI Agents","version":1},"reference_index":86,"source":"arxiv_source","source_observed_at":"2026-08-01T02:21:23.045209Z"},"links":{"citing_paper":"/paper/2607.25485"},"observation_digest":"sha256:10aa21f5e2465c7f9054635fd2b6d1be4d316fdee775d5b7181e25fc5eccf6bb","observation_id":"9d9d1c7a-3ec4-4c60-9e32-e9356c140530","resolution":{"observed_at":"2026-08-01T02:21:23.045209Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T02:21:23.128253Z","title":"and Haber, Nick , booktitle =","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.25485","last_updated":"2026-07-28T09:24:04Z","snapshot_observed_at":"2026-08-08T05:57:13.194969Z","submitted_at":"2026-07-28T09:24:04Z","title":"PatientAgentBench: A Benchmark Framework for Evaluating Patient-Facing Health AI Agents","version":1},"reference_index":87,"source":"arxiv_source","source_observed_at":"2026-08-01T02:21:23.128253Z"},"links":{"citing_paper":"/paper/2607.25485"},"observation_digest":"sha256:72dbc4f89100ec8d1ead9fa1155471e84e74ef56334721f26e603dee049a067c","observation_id":"c6c3f53f-d6c6-40ff-8e58-005d6c899190","resolution":{"observed_at":"2026-08-01T02:21:23.128253Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T02:21:23.176529Z","title":"FHIR-AgentBench: Benchmarking","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.25485","last_updated":"2026-07-28T09:24:04Z","snapshot_observed_at":"2026-08-08T05:57:13.194969Z","submitted_at":"2026-07-28T09:24:04Z","title":"PatientAgentBench: A Benchmark Framework for Evaluating Patient-Facing Health AI Agents","version":1},"reference_index":88,"source":"arxiv_source","source_observed_at":"2026-08-01T02:21:23.176529Z"},"links":{"citing_paper":"/paper/2607.25485"},"observation_digest":"sha256:87562a759bbd96bb1067e41c176e672ee902f5810231d2050931bd7d6deff247","observation_id":"d3ab3876-fa6a-44f1-8a0b-f4ccc7ee767c","resolution":{"observed_at":"2026-08-01T02:21:23.176529Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-01T02:21:23.227686Z","title":"Holistic Evaluation of Large Language Models for Medical Tasks with","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2607.25485","last_updated":"2026-07-28T09:24:04Z","snapshot_observed_at":"2026-08-08T05:57:13.194969Z","submitted_at":"2026-07-28T09:24:04Z","title":"PatientAgentBench: A Benchmark Framework for Evaluating Patient-Facing Health AI Agents","version":1},"reference_index":89,"source":"arxiv_source","source_observed_at":"2026-08-01T02:21:23.227686Z"},"links":{"citing_paper":"/paper/2607.25485"},"observation_digest":"sha256:1619a261bfe75d221801389230d011af3c83286db82cbf5a88677e8463f27cad","observation_id":"8c1426ff-2c85-4654-b9c8-6801953e1ae9","resolution":{"observed_at":"2026-08-01T02:21:23.227686Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2508.10925","last_updated":"2025-08-08T19:24:38Z","snapshot_observed_at":"2026-08-01T16:27:35.664983Z","submitted_at":"2025-08-08T19:24:38Z","title":"gpt-oss-120b & gpt-oss-20b Model Card","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2508.10925","snapshot_observed_at":"2026-08-01T02:21:23.281512Z","title":"doi:10.48550/arXiv.2508.10925 , url =","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.25485","last_updated":"2026-07-28T09:24:04Z","snapshot_observed_at":"2026-08-08T05:57:13.194969Z","submitted_at":"2026-07-28T09:24:04Z","title":"PatientAgentBench: A Benchmark Framework for Evaluating Patient-Facing Health AI Agents","version":1},"reference_index":90,"source":"arxiv_source","source_observed_at":"2026-08-01T02:21:23.281512Z"},"links":{"cited_paper":"/paper/2508.10925","citing_paper":"/paper/2607.25485"},"observation_digest":"sha256:34183da64ef986f3cc432818eb51ab5347ed6249bf6f6ca281259a8cbb5549a3","observation_id":"fc251de3-d568-45e1-9bb0-3ab4d26b4773","resolution":{"observed_at":"2026-08-01T02:21:23.281512Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2607.25485","last_updated":"2026-07-28T09:24:04Z","latest_version":1,"primary_category":"cs.AI","snapshot_observed_at":"2026-08-08T05:57:13.194969Z","submitted_at":"2026-07-28T09:24:04Z","title":"PatientAgentBench: A Benchmark Framework for Evaluating Patient-Facing Health AI Agents"},"reference_resolution":{"displayed":90,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":1,"unresolved":89,"verified_exact":0,"verified_fuzzy":0},"total_outbound_references":90},"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":"2026-08-08T06:32:00.761636+00:00","source":"crossref"},{"observed_at":"2026-08-08T06:31:55.24221+00:00","source":"retraction_watch"}],"thesis":"As of 8 August 2026, this Paper Citation Record lists 90 of 90 outbound references and 0 inbound Pith citation observations for arXiv:2607.25485."}