{"as_of":"2026-08-13T04:12:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:3b5b27d43f11723395e6b788b364d5f3a0413893219060b4aecd33da07f18487","coverage":[{"denominator":25,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":25,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-10T15:45:34.256340Z","state":"measured"},{"denominator":26,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":26,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-12T06:34:41.77262+00:00","state":"measured"},{"denominator":1,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":1,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-01T12:19:18.421552Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":1,"source":"pith","source_observed_at":"2026-08-05T02:28:24.338817Z","state":"measured"}],"external_citation_measurements":[{"count":0,"observed_at":"2026-08-05T02:28:24.338817Z","source":"pith"}],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2501.13687","last_updated":"2025-01-23T14:13:56Z","snapshot_observed_at":"2026-08-10T15:39:33.046206Z","submitted_at":"2025-01-23T14:13:56Z","title":"Question Answering on Patient Medical Records with Private Fine-Tuned LLMs","version":1},"cited_work":{"arxiv_id":"2501.13687","doi":"10.48550/arxiv.2501.13687","metadata_source":"pith","pith_arxiv_id":"2501.13687","snapshot_observed_at":"2026-08-05T02:49:54.815029Z","title":"Question Answering on Patient Medical Records with Private Fine-Tuned LLMs","venue":"cs.CL","work_id":"281ff7c4-0052-47b9-ba55-2fa9605a6940","year":2025},"citing_paper":{"arxiv_id":"2607.19604","last_updated":"2026-07-21T22:09:55Z","snapshot_observed_at":"2026-08-11T11:54:21.717965Z","submitted_at":"2026-07-21T22:09:55Z","title":"Scaling Laws for Hypernetwork-Based Knowledge Injection in Large Language Models","version":1},"reference_index":36,"source":"arxiv_source","source_observed_at":"2026-08-01T12:19:18.421552Z"},"links":{"cited_paper":"/paper/2501.13687","citing_paper":"/paper/2607.19604"},"observation_digest":"sha256:3bcde45aa4c00f774b087506895bfe2acc1e27b2cb6e93234d6cc866b395f661","observation_id":"f191d92e-8868-4655-aabe-326a0ea23a1f","resolution":{"observed_at":"2026-08-01T12:23:39.909062Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2501.13687/citation-record","integrity":"/paper/2501.13687/integrity","json":"/paper/2501.13687/citation-record.json","paper":"/paper/2501.13687"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T15:45:34.650752Z","title":"https://www.cms.gov/priorities/key-initiatives/ burden-reduction/interoperability/policies-and-regulations/ cms-interoperability-and-patient-access-final-rule-cms-9115-f","venue":null,"work_id":"40f33a88-e237-4cdf-9509-d52f48c9db88","year":2024},"citing_paper":{"arxiv_id":"2501.13687","last_updated":"2025-01-23T14:13:56Z","snapshot_observed_at":"2026-08-10T15:39:33.046206Z","submitted_at":"2025-01-23T14:13:56Z","title":"Question Answering on Patient Medical Records with Private Fine-Tuned LLMs","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-10T15:45:34.135384Z"},"links":{"citing_paper":"/paper/2501.13687"},"observation_digest":"sha256:9666ade637196021980242d8ca76f0db1fe0cbe0643883f2b232d4e25c83ffce","observation_id":"0eb42885-6c5b-406a-aca3-06e991ba8119","resolution":{"observed_at":"2026-08-10T15:45:34.656020Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T15:45:34.633825Z","title":"Accession Number: PLAW-114publ255, PLAW-114publ255 Call Number: AE 2.110:, AE 2.110/3:, AE 2.110:114-255, AE 2.110:, AE 2.110/3:, AE 2.110:114-255 Source: DGPO, DGPO","venue":null,"work_id":"f12b53e6-0a53-441f-bef5-8316b2eca8b0","year":null},"citing_paper":{"arxiv_id":"2501.13687","last_updated":"2025-01-23T14:13:56Z","snapshot_observed_at":"2026-08-10T15:39:33.046206Z","submitted_at":"2025-01-23T14:13:56Z","title":"Question Answering on Patient Medical Records with Private Fine-Tuned LLMs","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-10T15:45:34.140877Z"},"links":{"citing_paper":"/paper/2501.13687"},"observation_digest":"sha256:ebfa4d8ccad1c9be220eb9f8afa335e432c982e2b1b96d601d1e2e0831eb5a4f","observation_id":"2549340e-035c-4f4e-8e69-3335da817daf","resolution":{"observed_at":"2026-08-10T15:45:34.639082Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T15:45:34.617879Z","title":"https://www.apple.com/healthcare/ health-records/","venue":null,"work_id":"8e038afb-2304-48ed-9cfa-c95584f82f05","year":2024},"citing_paper":{"arxiv_id":"2501.13687","last_updated":"2025-01-23T14:13:56Z","snapshot_observed_at":"2026-08-10T15:39:33.046206Z","submitted_at":"2025-01-23T14:13:56Z","title":"Question Answering on Patient Medical Records with Private Fine-Tuned LLMs","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-10T15:45:34.145845Z"},"links":{"citing_paper":"/paper/2501.13687"},"observation_digest":"sha256:fea454de45d52c71ad6e2b77cb0dc3998d25ad20c3e725eac0048940e12e4e69","observation_id":"67a6c207-53f8-41bd-a414-ee021f482915","resolution":{"observed_at":"2026-08-10T15:45:34.622829Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T15:45:34.601551Z","title":"Almutairi, Sulaiman Al Mashrafi, and Talib Al Kalbani","venue":null,"work_id":"d59efb15-b429-40b7-8ff5-336a2767d942","year":null},"citing_paper":{"arxiv_id":"2501.13687","last_updated":"2025-01-23T14:13:56Z","snapshot_observed_at":"2026-08-10T15:39:33.046206Z","submitted_at":"2025-01-23T14:13:56Z","title":"Question Answering on Patient Medical Records with Private Fine-Tuned LLMs","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-10T15:45:34.150735Z"},"links":{"citing_paper":"/paper/2501.13687"},"observation_digest":"sha256:dbd46481842ba7777cbe324ea28ceb0889e630ccdae2482eba4d1f39d737581d","observation_id":"a097e9b2-7af9-443f-bcc2-2f2adbbc6609","resolution":{"observed_at":"2026-08-10T15:45:34.606784Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2402.06196","last_updated":"2025-03-23T14:51:01Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-02-09T05:37:09Z","title":"Large Language Models: A Survey","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.06196","snapshot_observed_at":"2026-08-10T15:45:34.155667Z","title":"https://arxiv.org/abs/2402.06196","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2501.13687","last_updated":"2025-01-23T14:13:56Z","snapshot_observed_at":"2026-08-10T15:39:33.046206Z","submitted_at":"2025-01-23T14:13:56Z","title":"Question Answering on Patient Medical Records with Private Fine-Tuned LLMs","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-10T15:45:34.155667Z"},"links":{"cited_paper":"/paper/2402.06196","citing_paper":"/paper/2501.13687"},"observation_digest":"sha256:41d603bc68bf06976968f6fca4a53e0f25cad27955f04720ab1f5e6851e9f547","observation_id":"cb5e0637-deea-4cc6-800c-07be150da4c0","resolution":{"observed_at":"2026-08-10T15:45:34.155667Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T15:45:34.584428Z","title":"Health information privacy","venue":null,"work_id":"3f232ba4-2f5f-4435-87bb-c869cfe466e4","year":2024},"citing_paper":{"arxiv_id":"2501.13687","last_updated":"2025-01-23T14:13:56Z","snapshot_observed_at":"2026-08-10T15:39:33.046206Z","submitted_at":"2025-01-23T14:13:56Z","title":"Question Answering on Patient Medical Records with Private Fine-Tuned LLMs","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-10T15:45:34.161375Z"},"links":{"citing_paper":"/paper/2501.13687"},"observation_digest":"sha256:ee314873fc02927ce8cae2429eb01d53b33bc97a503dc7587eab7040ce24891e","observation_id":"facf8f67-46e4-4b07-b351-5b96c5a19854","resolution":{"observed_at":"2026-08-10T15:45:34.589637Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T15:45:34.568036Z","title":null,"venue":null,"work_id":"e6aa7ac9-11ca-4f0e-ad03-e5efa7ea7b30","year":null},"citing_paper":{"arxiv_id":"2501.13687","last_updated":"2025-01-23T14:13:56Z","snapshot_observed_at":"2026-08-10T15:39:33.046206Z","submitted_at":"2025-01-23T14:13:56Z","title":"Question Answering on Patient Medical Records with Private Fine-Tuned LLMs","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-10T15:45:34.167188Z"},"links":{"citing_paper":"/paper/2501.13687"},"observation_digest":"sha256:03ed898fe5ad2495a991316cef01c9fa2dcaafbefa98fd87c0409f1e4197de16","observation_id":"43c52a00-16d7-49e3-be68-8bfd5b502a7c","resolution":{"observed_at":"2026-08-10T15:45:34.573149Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T15:45:34.551189Z","title":null,"venue":null,"work_id":"83720458-df08-489d-9d87-fe360e18fbc9","year":null},"citing_paper":{"arxiv_id":"2501.13687","last_updated":"2025-01-23T14:13:56Z","snapshot_observed_at":"2026-08-10T15:39:33.046206Z","submitted_at":"2025-01-23T14:13:56Z","title":"Question Answering on Patient Medical Records with Private Fine-Tuned LLMs","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-10T15:45:34.172787Z"},"links":{"citing_paper":"/paper/2501.13687"},"observation_digest":"sha256:dcbe6333cca12667af1e7e8020859f46a5cdbed633270c87c0abadadc4e39475","observation_id":"20f9c8b4-1be7-4c96-a866-52dd743a4787","resolution":{"observed_at":"2026-08-10T15:45:34.556105Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T15:45:34.534970Z","title":"LLaMA: Open and efficient foundation language models","venue":null,"work_id":"f78a78af-cd5a-43bd-b0e1-765988c5589f","year":null},"citing_paper":{"arxiv_id":"2501.13687","last_updated":"2025-01-23T14:13:56Z","snapshot_observed_at":"2026-08-10T15:39:33.046206Z","submitted_at":"2025-01-23T14:13:56Z","title":"Question Answering on Patient Medical Records with Private Fine-Tuned LLMs","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-10T15:45:34.177534Z"},"links":{"citing_paper":"/paper/2501.13687"},"observation_digest":"sha256:df2b3ce4a3a946ddacb76de7eea73a544b33588505d7b20de70e7e13b5907371","observation_id":"98a554d3-185a-474f-9a4c-6e6d4f98ce9b","resolution":{"observed_at":"2026-08-10T15:45:34.540043Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T15:45:34.518968Z","title":null,"venue":null,"work_id":"9febe0d0-3c56-4812-a744-8d499336c93a","year":2024},"citing_paper":{"arxiv_id":"2501.13687","last_updated":"2025-01-23T14:13:56Z","snapshot_observed_at":"2026-08-10T15:39:33.046206Z","submitted_at":"2025-01-23T14:13:56Z","title":"Question Answering on Patient Medical Records with Private Fine-Tuned LLMs","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-10T15:45:34.182529Z"},"links":{"citing_paper":"/paper/2501.13687"},"observation_digest":"sha256:8ea70f4e86b9ba5d27c31140fc7e597848ae51af1a26de79046d2b57efddbfac","observation_id":"e5210ea5-d2b2-43d4-826e-5cecde08bdea","resolution":{"observed_at":"2026-08-10T15:45:34.523754Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T15:45:34.187926Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2501.13687","last_updated":"2025-01-23T14:13:56Z","snapshot_observed_at":"2026-08-10T15:39:33.046206Z","submitted_at":"2025-01-23T14:13:56Z","title":"Question Answering on Patient Medical Records with Private Fine-Tuned LLMs","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-10T15:45:34.187926Z"},"links":{"citing_paper":"/paper/2501.13687"},"observation_digest":"sha256:ddf982705856878c462920e2b2e7c33b71281349baee651937721081135f09cd","observation_id":"56b3fd56-8740-4b8f-bcb3-caf0a8126196","resolution":{"observed_at":"2026-08-10T15:45:34.187926Z","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":"2026-08-10T15:45:34.193297Z","title":"Parameter-efficient transfer learning for nlp","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2501.13687","last_updated":"2025-01-23T14:13:56Z","snapshot_observed_at":"2026-08-10T15:39:33.046206Z","submitted_at":"2025-01-23T14:13:56Z","title":"Question Answering on Patient Medical Records with Private Fine-Tuned LLMs","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-10T15:45:34.193297Z"},"links":{"citing_paper":"/paper/2501.13687"},"observation_digest":"sha256:4cf3e26c3c2b14b852ebb07c1f6188fc7df6c424aa709864fd26e52eb6fcfafa","observation_id":"204050e4-7b3c-4e0e-9b11-fcc4bf2d96f1","resolution":{"observed_at":"2026-08-10T15:45:34.193297Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T15:45:34.481241Z","title":"Hu, Yelong Shen, Phillip Wallis, Zeyuan Allen-Zhu, Yuanzhi Li, Shean Wang, Lu Wang, and Weizhu Chen","venue":null,"work_id":"250d17fb-7c4f-4313-bf8f-8b2adfbcaef5","year":null},"citing_paper":{"arxiv_id":"2501.13687","last_updated":"2025-01-23T14:13:56Z","snapshot_observed_at":"2026-08-10T15:39:33.046206Z","submitted_at":"2025-01-23T14:13:56Z","title":"Question Answering on Patient Medical Records with Private Fine-Tuned LLMs","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-10T15:45:34.198686Z"},"links":{"citing_paper":"/paper/2501.13687"},"observation_digest":"sha256:f476cb938a35fcb57a4bbd8dc77e421326726816b377c6bc918014dc16f41943","observation_id":"da56cbb5-46bc-4033-ad4b-be5502ea78fb","resolution":{"observed_at":"2026-08-10T15:45:34.486104Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T15:45:34.464295Z","title":"QLoRA: Efficient finetuning of quantized LLMs","venue":null,"work_id":"5a8e6609-a4cb-4038-ae22-baa93b3e0d5b","year":null},"citing_paper":{"arxiv_id":"2501.13687","last_updated":"2025-01-23T14:13:56Z","snapshot_observed_at":"2026-08-10T15:39:33.046206Z","submitted_at":"2025-01-23T14:13:56Z","title":"Question Answering on Patient Medical Records with Private Fine-Tuned LLMs","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-10T15:45:34.204216Z"},"links":{"citing_paper":"/paper/2501.13687"},"observation_digest":"sha256:5397f5b389491ef1357fd87ad57794c06731a3dd3628c4ec821e656c94c836bd","observation_id":"87626ec7-d256-4cdc-8b0f-42247a60b2a7","resolution":{"observed_at":"2026-08-10T15:45:34.469519Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T15:45:34.447756Z","title":"Yerebakan, Yoshihisa Shinagawa, and Yuan Luo","venue":null,"work_id":"fdff5d2c-568d-4aa1-a4ac-24a963898dae","year":2023},"citing_paper":{"arxiv_id":"2501.13687","last_updated":"2025-01-23T14:13:56Z","snapshot_observed_at":"2026-08-10T15:39:33.046206Z","submitted_at":"2025-01-23T14:13:56Z","title":"Question Answering on Patient Medical Records with Private Fine-Tuned LLMs","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-10T15:45:34.209067Z"},"links":{"citing_paper":"/paper/2501.13687"},"observation_digest":"sha256:37aa718b793015388521cc389e3c79542be4fdc301174e6f834680d50ad32b33","observation_id":"a25afa51-f2de-4933-8dae-a019874452af","resolution":{"observed_at":"2026-08-10T15:45:34.452720Z","resolver_source":"raw_fallback","status":"malformed_identifier"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T15:45:34.432304Z","title":"Agentic LLM workflows for generating patient-friendly medical reports","venue":null,"work_id":"34d73fe2-6fea-4d5f-b6b1-6bf14d89ec19","year":null},"citing_paper":{"arxiv_id":"2501.13687","last_updated":"2025-01-23T14:13:56Z","snapshot_observed_at":"2026-08-10T15:39:33.046206Z","submitted_at":"2025-01-23T14:13:56Z","title":"Question Answering on Patient Medical Records with Private Fine-Tuned LLMs","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-10T15:45:34.213873Z"},"links":{"citing_paper":"/paper/2501.13687"},"observation_digest":"sha256:1c71233c7797ac7e3ea23a84592447e5039c55a8ea7d1db94f73eb479af735ea","observation_id":"5971e233-32f0-4bb1-8dfb-5111d02792eb","resolution":{"observed_at":"2026-08-10T15:45:34.437404Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T15:45:34.415924Z","title":"LLM on FHIR – demystifying health records","venue":null,"work_id":"923ec3dd-5043-40b2-be98-1cdfae1873a2","year":null},"citing_paper":{"arxiv_id":"2501.13687","last_updated":"2025-01-23T14:13:56Z","snapshot_observed_at":"2026-08-10T15:39:33.046206Z","submitted_at":"2025-01-23T14:13:56Z","title":"Question Answering on Patient Medical Records with Private Fine-Tuned LLMs","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-10T15:45:34.218825Z"},"links":{"citing_paper":"/paper/2501.13687"},"observation_digest":"sha256:3d7bc6a632bd48e75fd2e26f6c92cc25314f7c7d6f3e037465989dfaf92e8d1a","observation_id":"e7057d94-0280-40c4-92d4-95692ac1d308","resolution":{"observed_at":"2026-08-10T15:45:34.421156Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T15:45:34.400280Z","title":"SUPaHOT: Universally scalable and private method to demystify FHIR health records","venue":null,"work_id":"5001400a-4d72-4410-9c22-a2c7c6c386e6","year":null},"citing_paper":{"arxiv_id":"2501.13687","last_updated":"2025-01-23T14:13:56Z","snapshot_observed_at":"2026-08-10T15:39:33.046206Z","submitted_at":"2025-01-23T14:13:56Z","title":"Question Answering on Patient Medical Records with Private Fine-Tuned LLMs","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-10T15:45:34.223420Z"},"links":{"citing_paper":"/paper/2501.13687"},"observation_digest":"sha256:a7ffd155179cb67a797fc38b8ebe8e859ed660d6958bb001e94c1f62ed5830ae","observation_id":"ead83b0a-9d8b-4b4c-8243-5d2e862eb436","resolution":{"observed_at":"2026-08-10T15:45:34.405442Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T15:45:34.384226Z","title":"Meditron-7b: Scaling medical pretraining for large language models, 2023","venue":null,"work_id":"06758079-47ca-4b94-ba32-f79921f73c0c","year":2023},"citing_paper":{"arxiv_id":"2501.13687","last_updated":"2025-01-23T14:13:56Z","snapshot_observed_at":"2026-08-10T15:39:33.046206Z","submitted_at":"2025-01-23T14:13:56Z","title":"Question Answering on Patient Medical Records with Private Fine-Tuned LLMs","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-10T15:45:34.228343Z"},"links":{"citing_paper":"/paper/2501.13687"},"observation_digest":"sha256:127e0d1a9984decb605668396d17e7a8a37c369704f58628804ce44a28f31f63","observation_id":"71d3e698-bb86-4c11-8b64-ecbe9316ada1","resolution":{"observed_at":"2026-08-10T15:45:34.389360Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T15:45:34.233118Z","title":"Retrieval-augmented generation for large language models: A survey, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2501.13687","last_updated":"2025-01-23T14:13:56Z","snapshot_observed_at":"2026-08-10T15:39:33.046206Z","submitted_at":"2025-01-23T14:13:56Z","title":"Question Answering on Patient Medical Records with Private Fine-Tuned LLMs","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-10T15:45:34.233118Z"},"links":{"citing_paper":"/paper/2501.13687"},"observation_digest":"sha256:25c1dbdb502d5106825d8bc311d4e0b9aef6feb68104a33056aed1d20621a028","observation_id":"fdddbd38-e3fd-4478-9e4d-7f5beb3c44f2","resolution":{"observed_at":"2026-08-10T15:45:34.233118Z","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":"2026-08-10T15:45:34.238363Z","title":"Retrieval-augmented generation for natural language processing: A survey, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2501.13687","last_updated":"2025-01-23T14:13:56Z","snapshot_observed_at":"2026-08-10T15:39:33.046206Z","submitted_at":"2025-01-23T14:13:56Z","title":"Question Answering on Patient Medical Records with Private Fine-Tuned LLMs","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-10T15:45:34.238363Z"},"links":{"citing_paper":"/paper/2501.13687"},"observation_digest":"sha256:4dd143e148c6f4122a319ad119c4fe16615bc60358ed744f5a6ffe24a68eaa51","observation_id":"eab18689-774b-4699-9c05-d2ae1ec2734b","resolution":{"observed_at":"2026-08-10T15:45:34.238363Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T15:45:34.348483Z","title":"Synthea: An approach, method, and software mechanism for generating synthetic patients and the synthetic electronic health care record","venue":null,"work_id":"78f6bf78-574b-415b-8e8c-4012b32503c5","year":null},"citing_paper":{"arxiv_id":"2501.13687","last_updated":"2025-01-23T14:13:56Z","snapshot_observed_at":"2026-08-10T15:39:33.046206Z","submitted_at":"2025-01-23T14:13:56Z","title":"Question Answering on Patient Medical Records with Private Fine-Tuned LLMs","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-10T15:45:34.242945Z"},"links":{"citing_paper":"/paper/2501.13687"},"observation_digest":"sha256:96dee0c79c900f0ac7cb085601f420424c2db4bae204a108654ce87c598c7b6e","observation_id":"8031b67b-255a-42e8-8a7a-991ea4740d07","resolution":{"observed_at":"2026-08-10T15:45:34.353412Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T15:45:34.247499Z","title":"Meteor: An automatic metric for mt evaluation with improved correlation with human judgments","venue":null,"work_id":null,"year":2005},"citing_paper":{"arxiv_id":"2501.13687","last_updated":"2025-01-23T14:13:56Z","snapshot_observed_at":"2026-08-10T15:39:33.046206Z","submitted_at":"2025-01-23T14:13:56Z","title":"Question Answering on Patient Medical Records with Private Fine-Tuned LLMs","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-10T15:45:34.247499Z"},"links":{"citing_paper":"/paper/2501.13687"},"observation_digest":"sha256:a4dcd4479a4f052710abce6f1142f89f052d54287c45b812735cdfc1393a7a53","observation_id":"d6215040-c7bc-4e18-8ee4-e9ab0acaea31","resolution":{"observed_at":"2026-08-10T15:45:34.247499Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T15:45:34.322216Z","title":"LLMs as narcissistic evaluators: When ego inflates evaluation scores","venue":null,"work_id":"ed98597d-59c7-4133-887f-cc91cac600e8","year":null},"citing_paper":{"arxiv_id":"2501.13687","last_updated":"2025-01-23T14:13:56Z","snapshot_observed_at":"2026-08-10T15:39:33.046206Z","submitted_at":"2025-01-23T14:13:56Z","title":"Question Answering on Patient Medical Records with Private Fine-Tuned LLMs","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-10T15:45:34.251850Z"},"links":{"citing_paper":"/paper/2501.13687"},"observation_digest":"sha256:71ca58c0ac3996d39438516327ee2dca3ee71b8cb68438d2760f63674576196b","observation_id":"6335fc35-8082-4c08-a8f8-50351c8d985e","resolution":{"observed_at":"2026-08-10T15:45:34.327954Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T15:45:34.305256Z","title":"resource","venue":null,"work_id":"4b8f31ca-b761-47b4-9347-5ed836c2c0ae","year":2018},"citing_paper":{"arxiv_id":"2501.13687","last_updated":"2025-01-23T14:13:56Z","snapshot_observed_at":"2026-08-10T15:39:33.046206Z","submitted_at":"2025-01-23T14:13:56Z","title":"Question Answering on Patient Medical Records with Private Fine-Tuned LLMs","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-10T15:45:34.256340Z"},"links":{"citing_paper":"/paper/2501.13687"},"observation_digest":"sha256:b51288a36ed8444b80e814ba2610e51d1eb728a76f7bee980cb2c3b277686b10","observation_id":"68378e82-e3bd-445f-93bb-1b966b7108a3","resolution":{"observed_at":"2026-08-10T15:45:34.311034Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2501.13687","last_updated":"2025-01-23T14:13:56Z","latest_version":1,"primary_category":"cs.CL","snapshot_observed_at":"2026-08-10T15:39:33.046206Z","submitted_at":"2025-01-23T14:13:56Z","title":"Question Answering on Patient Medical Records with Private Fine-Tuned LLMs"},"reference_resolution":{"displayed":25,"state_counts":{"malformed_identifier":1,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":9,"verified_exact":0,"verified_fuzzy":15},"total_outbound_references":25},"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":"2026-08-12T06:34:41.77262+00:00","source":"crossref"},{"observed_at":"2026-08-12T06:34:36.333875+00:00","source":"retraction_watch"}],"thesis":"As of 13 August 2026, this Paper Citation Record lists 25 of 25 outbound references and 1 inbound Pith citation observation for arXiv:2501.13687."}