{"as_of":"2026-08-09T14:52:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:3344e4da428644b5710f3f17a666ff1816543ae233c9ff4e8eb85ece9aaff9da","coverage":[{"denominator":0,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":11,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":11,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-09T06:31:02.800959+00:00","state":"measured"},{"denominator":11,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":11,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-08T17:37:07.089039Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"arxiv_reference","source_observed_at":"2026-05-21T11:00:02.191670Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2402.02803","last_updated":"2025-01-27T04:30:43Z","snapshot_observed_at":"2026-08-09T06:42:06.996974Z","submitted_at":"2024-02-05T08:25:22Z","title":"Large Language Model Distilling Medication Recommendation Model","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.02803","snapshot_observed_at":"2026-08-08T17:37:07.089039Z","title":"Large Language Model Distilling Medication Recommendation Model , February 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2503.16433","last_updated":"2025-02-09T12:46:13Z","snapshot_observed_at":"2026-08-09T02:52:49.763060Z","submitted_at":"2025-02-09T12:46:13Z","title":"The Application of MATEC (Multi-AI Agent Team Care) Framework in Sepsis Care","version":1},"reference_index":14,"source":"arxiv_source","source_observed_at":"2026-08-08T17:37:07.089039Z"},"links":{"cited_paper":"/paper/2402.02803","citing_paper":"/paper/2503.16433"},"observation_digest":"sha256:7858fda937adb9055d12c5353664c32e83aa0d9cef0daeb922589915dcd94dfa","observation_id":"1e1916c6-17fd-4670-bc6e-b8573043a2c9","resolution":{"observed_at":"2026-08-08T17:37:07.089039Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2402.02803","last_updated":"2025-01-27T04:30:43Z","snapshot_observed_at":"2026-08-09T06:42:06.996974Z","submitted_at":"2024-02-05T08:25:22Z","title":"Large Language Model Distilling Medication Recommendation Model","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.02803","snapshot_observed_at":"2026-08-07T14:39:31.452202Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.18120","last_updated":"2025-05-23T17:21:14Z","snapshot_observed_at":"2026-08-09T06:43:18.704583Z","submitted_at":"2025-05-23T17:21:14Z","title":"Bidirectional Knowledge Distillation for Enhancing Sequential Recommendation with Large Language Models","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-07T14:39:31.452202Z"},"links":{"cited_paper":"/paper/2402.02803","citing_paper":"/paper/2505.18120"},"observation_digest":"sha256:a5980181d2246e3a2dad4770c7a5772207d5650602d277e23aa9c39c9b9482a0","observation_id":"7fec4eb1-9b48-44b3-b22b-a56a23884396","resolution":{"observed_at":"2026-08-07T14:39:31.452202Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2402.02803","last_updated":"2025-01-27T04:30:43Z","snapshot_observed_at":"2026-08-09T06:42:06.996974Z","submitted_at":"2024-02-05T08:25:22Z","title":"Large Language Model Distilling Medication Recommendation Model","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.02803","snapshot_observed_at":"2026-08-07T00:59:43.753283Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.12379","last_updated":"2025-06-14T07:21:11Z","snapshot_observed_at":"2026-08-07T23:12:16.942292Z","submitted_at":"2025-06-14T07:21:11Z","title":"Training-free LLM Merging for Multi-task Learning","version":1},"reference_index":24,"source":"arxiv_source","source_observed_at":"2026-08-07T00:59:43.753283Z"},"links":{"cited_paper":"/paper/2402.02803","citing_paper":"/paper/2506.12379"},"observation_digest":"sha256:fce6db30aacdf9eb15f4bbff0176ef84f8e0f583a27974450e318d7ed77b970a","observation_id":"a8e8256b-3d49-4968-bf31-508eb7679497","resolution":{"observed_at":"2026-08-07T00:59:43.753283Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2402.02803","last_updated":"2025-01-27T04:30:43Z","snapshot_observed_at":"2026-08-09T06:42:06.996974Z","submitted_at":"2024-02-05T08:25:22Z","title":"Large Language Model Distilling Medication Recommendation Model","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.02803","snapshot_observed_at":"2026-08-06T23:49:16.197184Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.16114","last_updated":"2026-06-01T12:57:38Z","snapshot_observed_at":"2026-08-06T23:41:57.606836Z","submitted_at":"2025-06-19T08:04:31Z","title":"GFlowGR: Fine-tuning Generative Recommendation Frameworks with Generative Flow Networks","version":3},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-06T23:49:16.197184Z"},"links":{"cited_paper":"/paper/2402.02803","citing_paper":"/paper/2506.16114"},"observation_digest":"sha256:11173628098d151af53e906aca5ba4489958f35cc87716df1c4ef71035cbb5ba","observation_id":"2ee662b9-e4c1-4005-8db7-9651cd618085","resolution":{"observed_at":"2026-08-06T23:49:16.197184Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2402.02803","last_updated":"2025-01-27T04:30:43Z","snapshot_observed_at":"2026-08-09T06:42:06.996974Z","submitted_at":"2024-02-05T08:25:22Z","title":"Large Language Model Distilling Medication Recommendation Model","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.02803","snapshot_observed_at":"2026-08-06T19:51:40.747628Z","title":"Large language model distilling medication rec- ommendation model","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.04428","last_updated":"2025-07-06T15:24:00Z","snapshot_observed_at":"2026-08-09T06:42:40.703851Z","submitted_at":"2025-07-06T15:24:00Z","title":"ARMR: Adaptively Responsive Network for Medication Recommendation","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-06T19:51:40.747628Z"},"links":{"cited_paper":"/paper/2402.02803","citing_paper":"/paper/2507.04428"},"observation_digest":"sha256:a295e19ee24b30f1b77064248592cce792a3b24db6917818930cd30de1d39c40","observation_id":"18e4d47f-9113-4477-8f56-c48c940fb186","resolution":{"observed_at":"2026-08-06T19:51:40.747628Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2402.02803","last_updated":"2025-01-27T04:30:43Z","snapshot_observed_at":"2026-08-09T06:42:06.996974Z","submitted_at":"2024-02-05T08:25:22Z","title":"Large Language Model Distilling Medication Recommendation Model","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.02803","snapshot_observed_at":"2026-08-05T19:02:42.866100Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2508.13579","last_updated":"2025-08-19T07:24:48Z","snapshot_observed_at":"2026-08-07T23:05:40.472292Z","submitted_at":"2025-08-19T07:24:48Z","title":"Toward Better EHR Reasoning in LLMs: Reinforcement Learning with Expert Attention Guidance","version":1},"reference_index":25,"source":"arxiv_source","source_observed_at":"2026-08-05T19:02:42.866100Z"},"links":{"cited_paper":"/paper/2402.02803","citing_paper":"/paper/2508.13579"},"observation_digest":"sha256:bc034fc43c0ff8211d78ca63a110ffde6b407fc8897e77ac776af1fd1848cb26","observation_id":"d693c96c-e866-45a2-a756-a5310e1c964c","resolution":{"observed_at":"2026-08-05T19:02:42.866100Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2402.02803","last_updated":"2025-01-27T04:30:43Z","snapshot_observed_at":"2026-08-09T06:42:06.996974Z","submitted_at":"2024-02-05T08:25:22Z","title":"Large Language Model Distilling Medication Recommendation Model","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.02803","snapshot_observed_at":"2026-08-05T12:03:48.395487Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.02017","last_updated":"2025-09-02T07:02:29Z","snapshot_observed_at":"2026-08-09T06:42:41.266508Z","submitted_at":"2025-09-02T07:02:29Z","title":"Empowering Large Language Model for Sequential Recommendation via Multimodal Embeddings and Semantic IDs","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-05T12:03:48.395487Z"},"links":{"cited_paper":"/paper/2402.02803","citing_paper":"/paper/2509.02017"},"observation_digest":"sha256:cb4e4222fce09e2643b1df7434f7ea153f8925bfc345ba897b91d96932402927","observation_id":"1163828a-2401-4e59-890b-9765a32e7d0b","resolution":{"observed_at":"2026-08-05T12:03:48.395487Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2402.02803","last_updated":"2025-01-27T04:30:43Z","snapshot_observed_at":"2026-08-09T06:42:06.996974Z","submitted_at":"2024-02-05T08:25:22Z","title":"Large Language Model Distilling Medication Recommendation Model","version":2},"cited_work":{"arxiv_id":"2402.02803","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2402.02803","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"arXiv preprint arXiv:2402.02803 (2024)","venue":null,"work_id":"e5423833-9234-4206-9649-c953d3e36e60","year":2024},"citing_paper":{"arxiv_id":"2605.06702","last_updated":"2026-05-05T12:16:59Z","snapshot_observed_at":"2026-08-02T07:43:25.285396Z","submitted_at":"2026-05-05T12:16:59Z","title":"CASCADE: Case-Based Continual Adaptation for Large Language Models During Deployment","version":1},"reference_index":96,"source":"pdf_text","source_observed_at":"2026-05-11T01:16:30.734428Z"},"links":{"cited_paper":"/paper/2402.02803","citing_paper":"/paper/2605.06702"},"observation_digest":"sha256:b7416eccef411f9879b8bff844fd69deff5d99e0a688b78c53f357d9d5990105","observation_id":"cf089749-e1ec-489d-ab2b-ca2045e75268","resolution":{"observed_at":"2026-05-11T04:30:59.799106Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2402.02803","last_updated":"2025-01-27T04:30:43Z","snapshot_observed_at":"2026-08-09T06:42:06.996974Z","submitted_at":"2024-02-05T08:25:22Z","title":"Large Language Model Distilling Medication Recommendation Model","version":2},"cited_work":{"arxiv_id":"2402.02803","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2402.02803","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"arXiv preprint arXiv:2402.02803 (2024)","venue":null,"work_id":"e5423833-9234-4206-9649-c953d3e36e60","year":2024},"citing_paper":{"arxiv_id":"2605.14543","last_updated":"2026-05-14T08:24:03Z","snapshot_observed_at":"2026-08-03T15:51:13.547851Z","submitted_at":"2026-05-14T08:24:03Z","title":"RxEval: A Prescription-Level Benchmark for Evaluating LLM Medication Recommendation","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-05-15T02:08:53.361260Z"},"links":{"cited_paper":"/paper/2402.02803","citing_paper":"/paper/2605.14543"},"observation_digest":"sha256:a8bedc1b82516856c6e35ee63f84a0a48d2c6b3d6788924f64db8f65704f658a","observation_id":"cb0e8527-be49-4efe-b2e3-73fb44f20000","resolution":{"observed_at":"2026-05-15T02:09:38.831850Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2402.02803","last_updated":"2025-01-27T04:30:43Z","snapshot_observed_at":"2026-08-09T06:42:06.996974Z","submitted_at":"2024-02-05T08:25:22Z","title":"Large Language Model Distilling Medication Recommendation Model","version":2},"cited_work":{"arxiv_id":"2402.02803","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2402.02803","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"arXiv preprint arXiv:2402.02803 (2024)","venue":null,"work_id":"e5423833-9234-4206-9649-c953d3e36e60","year":2024},"citing_paper":{"arxiv_id":"2605.20188","last_updated":"2026-03-21T15:10:54Z","snapshot_observed_at":"2026-07-25T23:21:30.037024Z","submitted_at":"2026-03-21T15:10:54Z","title":"GraphDiffMed: Knowledge-Constrained Differential Attention with Pharmacological Graph Priors for Medication Recommendation","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-05-21T10:56:29.430340Z"},"links":{"cited_paper":"/paper/2402.02803","citing_paper":"/paper/2605.20188"},"observation_digest":"sha256:251ce0d98812f86b1329cfc6e6402936c98319c6a1017677bea6ae25976d27e3","observation_id":"bab84dff-39d7-4230-86cf-ac2360b53c99","resolution":{"observed_at":"2026-05-21T11:00:02.194193Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2402.02803","last_updated":"2025-01-27T04:30:43Z","snapshot_observed_at":"2026-08-09T06:42:06.996974Z","submitted_at":"2024-02-05T08:25:22Z","title":"Large Language Model Distilling Medication Recommendation Model","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.02803","snapshot_observed_at":"2026-08-01T09:10:46.275895Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.24829","last_updated":"2026-07-23T02:48:23Z","snapshot_observed_at":"2026-08-07T02:44:39.896522Z","submitted_at":"2026-07-23T02:48:23Z","title":"Improving Rare Medication Recommendation with Counterfactual Data Augmentation and Large Language Models","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-01T09:10:46.275895Z"},"links":{"cited_paper":"/paper/2402.02803","citing_paper":"/paper/2607.24829"},"observation_digest":"sha256:86aaa0874fc9ed6d1c57b62e9eeca7782c20351391c2f0c8f4ca845ed53849ab","observation_id":"50e98cb6-c4aa-4bfd-ac77-4d376408ef69","resolution":{"observed_at":"2026-08-01T09:10:46.275895Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2402.02803/citation-record","integrity":"/paper/2402.02803/integrity","json":"/paper/2402.02803/citation-record.json","paper":"/paper/2402.02803"},"outbound":[],"paper":{"arxiv_id":"2402.02803","last_updated":"2025-01-27T04:30:43Z","latest_version":2,"primary_category":"cs.IR","snapshot_observed_at":"2026-08-09T06:42:06.996974Z","submitted_at":"2024-02-05T08:25:22Z","title":"Large Language Model Distilling Medication Recommendation Model"},"reference_resolution":{"displayed":0,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":0,"verified_exact":0,"verified_fuzzy":0},"total_outbound_references":0},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"thesis":"As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 11 inbound Pith citation observations for arXiv:2402.02803."}