{"as_of":"2026-08-12T05:20:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:5d0fda6fde5bd1b15da75048967dbb97b3d74aa59246f427798d3d25e34365d3","coverage":[{"denominator":41,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":41,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-10T16:54:44.030480Z","state":"measured"},{"denominator":41,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":41,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-11T06:34:44.6726+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/2501.12746/citation-record","integrity":"/paper/2501.12746/integrity","json":"/paper/2501.12746/citation-record.json","paper":"/paper/2501.12746"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T16:54:43.854626Z","title":"online\" 'onlinestring :=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2501.12746","last_updated":"2025-02-14T01:02:04Z","snapshot_observed_at":"2026-08-11T19:53:12.706625Z","submitted_at":"2025-01-22T09:27:11Z","title":"EvidenceMap: Learning Evidence Analysis to Unleash the Power of Small Language Models for Biomedical Question Answering","version":4},"reference_index":1,"source":"arxiv_source","source_observed_at":"2026-08-10T16:54:43.854626Z"},"links":{"citing_paper":"/paper/2501.12746"},"observation_digest":"sha256:22446fa13906cb0b16e42f9b93591c061d545d0cba393b8567828cf8013c0d76","observation_id":"2d0431e3-e9fc-485c-a332-9dd55d1184aa","resolution":{"observed_at":"2026-08-10T16:54:43.854626Z","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":"2026-08-10T16:54:43.859974Z","title":"write newline","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2501.12746","last_updated":"2025-02-14T01:02:04Z","snapshot_observed_at":"2026-08-11T19:53:12.706625Z","submitted_at":"2025-01-22T09:27:11Z","title":"EvidenceMap: Learning Evidence Analysis to Unleash the Power of Small Language Models for Biomedical Question Answering","version":4},"reference_index":2,"source":"arxiv_source","source_observed_at":"2026-08-10T16:54:43.859974Z"},"links":{"citing_paper":"/paper/2501.12746"},"observation_digest":"sha256:50bfaaa1d9f06ddc079cc727c30b4cd0a0988c830108742863316f6b65bc00c4","observation_id":"75c744d2-1217-4196-89d7-5d75b5d3d3ea","resolution":{"observed_at":"2026-08-10T16:54:43.859974Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2404.14219","last_updated":"2024-08-30T21:17:17Z","snapshot_observed_at":"2026-08-10T14:07:02.234322Z","submitted_at":"2024-04-22T14:32:33Z","title":"Phi-3 Technical Report: A Highly Capable Language Model Locally on Your Phone","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.14219","snapshot_observed_at":"2026-08-10T16:54:43.864907Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2501.12746","last_updated":"2025-02-14T01:02:04Z","snapshot_observed_at":"2026-08-11T19:53:12.706625Z","submitted_at":"2025-01-22T09:27:11Z","title":"EvidenceMap: Learning Evidence Analysis to Unleash the Power of Small Language Models for Biomedical Question Answering","version":4},"reference_index":3,"source":"arxiv_source","source_observed_at":"2026-08-10T16:54:43.864907Z"},"links":{"cited_paper":"/paper/2404.14219","citing_paper":"/paper/2501.12746"},"observation_digest":"sha256:b47588e67d9ebb428b71f61a44856f0528615e3327642933d8abcb49a1705f7f","observation_id":"8c53ac28-af84-433b-af86-1f91d30b9ecf","resolution":{"observed_at":"2026-08-10T16:54:43.864907Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2310.11511","last_updated":"2023-10-17T18:18:32Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-10-17T18:18:32Z","title":"Self-RAG: Learning to Retrieve, Generate, and Critique through Self-Reflection","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.11511","snapshot_observed_at":"2026-08-10T16:54:43.872404Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2501.12746","last_updated":"2025-02-14T01:02:04Z","snapshot_observed_at":"2026-08-11T19:53:12.706625Z","submitted_at":"2025-01-22T09:27:11Z","title":"EvidenceMap: Learning Evidence Analysis to Unleash the Power of Small Language Models for Biomedical Question Answering","version":4},"reference_index":4,"source":"arxiv_source","source_observed_at":"2026-08-10T16:54:43.872404Z"},"links":{"cited_paper":"/paper/2310.11511","citing_paper":"/paper/2501.12746"},"observation_digest":"sha256:93d2c30a902c0f689aca672ba2f441c4e68b28a93384db0f1a8ab4eab74d4e84","observation_id":"758e1cdd-2320-4340-9c21-2c4a819cb690","resolution":{"observed_at":"2026-08-10T16:54:43.872404Z","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":"2026-08-10T16:54:44.535401Z","title":null,"venue":null,"work_id":"9295f382-cb0e-49cb-8f7f-05694eb81200","year":2021},"citing_paper":{"arxiv_id":"2501.12746","last_updated":"2025-02-14T01:02:04Z","snapshot_observed_at":"2026-08-11T19:53:12.706625Z","submitted_at":"2025-01-22T09:27:11Z","title":"EvidenceMap: Learning Evidence Analysis to Unleash the Power of Small Language Models for Biomedical Question Answering","version":4},"reference_index":5,"source":"arxiv_source","source_observed_at":"2026-08-10T16:54:43.877413Z"},"links":{"citing_paper":"/paper/2501.12746"},"observation_digest":"sha256:fe52387f8b0a153b5724f93ed349b011e453b2f6de94236070f8b5d2e752752e","observation_id":"87fe68c2-9713-4c9c-8cd5-0853dfd2f30e","resolution":{"observed_at":"2026-08-10T16:54:44.538916Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-10T16:54:43.881886Z","title":null,"venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2501.12746","last_updated":"2025-02-14T01:02:04Z","snapshot_observed_at":"2026-08-11T19:53:12.706625Z","submitted_at":"2025-01-22T09:27:11Z","title":"EvidenceMap: Learning Evidence Analysis to Unleash the Power of Small Language Models for Biomedical Question Answering","version":4},"reference_index":6,"source":"arxiv_source","source_observed_at":"2026-08-10T16:54:43.881886Z"},"links":{"citing_paper":"/paper/2501.12746"},"observation_digest":"sha256:c7231fe07df4f8cb1f8d5d233c5551e870db3b8c884d238e1dcca212ba606839","observation_id":"fb2e846b-4be5-4c5c-b9cc-f52ac234bf83","resolution":{"observed_at":"2026-08-10T16:54:43.881886Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2407.21783","last_updated":"2024-11-23T23:27:33Z","snapshot_observed_at":"2026-08-10T16:40:37.411115Z","submitted_at":"2024-07-31T17:54:27Z","title":"The Llama 3 Herd of Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2407.21783","snapshot_observed_at":"2026-08-10T16:54:43.887292Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2501.12746","last_updated":"2025-02-14T01:02:04Z","snapshot_observed_at":"2026-08-11T19:53:12.706625Z","submitted_at":"2025-01-22T09:27:11Z","title":"EvidenceMap: Learning Evidence Analysis to Unleash the Power of Small Language Models for Biomedical Question Answering","version":4},"reference_index":7,"source":"arxiv_source","source_observed_at":"2026-08-10T16:54:43.887292Z"},"links":{"cited_paper":"/paper/2407.21783","citing_paper":"/paper/2501.12746"},"observation_digest":"sha256:9e523d2ce53249127bab5b1000cbb6ff154bba6f4c316ad7e23842c7d15c584f","observation_id":"a5f28198-a62d-4636-81a1-c45cb2970b59","resolution":{"observed_at":"2026-08-10T16:54:43.887292Z","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":"2026-08-10T16:54:44.522773Z","title":null,"venue":null,"work_id":"9a0f15e7-3857-46f4-9fb8-b134d0fd9a94","year":2024},"citing_paper":{"arxiv_id":"2501.12746","last_updated":"2025-02-14T01:02:04Z","snapshot_observed_at":"2026-08-11T19:53:12.706625Z","submitted_at":"2025-01-22T09:27:11Z","title":"EvidenceMap: Learning Evidence Analysis to Unleash the Power of Small Language Models for Biomedical Question Answering","version":4},"reference_index":8,"source":"arxiv_source","source_observed_at":"2026-08-10T16:54:43.892298Z"},"links":{"citing_paper":"/paper/2501.12746"},"observation_digest":"sha256:df036d0f7ca21b3efee9d39cf947e2ef4f153c3622e25710aba8aef7fd292db7","observation_id":"011b8671-169d-4b0e-a7ec-567688f136a2","resolution":{"observed_at":"2026-08-10T16:54:44.527196Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2312.10997","last_updated":"2024-03-27T09:16:57Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-12-18T07:47:33Z","title":"Retrieval-Augmented Generation for Large Language Models: A Survey","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2312.10997","snapshot_observed_at":"2026-08-10T16:54:43.896802Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2501.12746","last_updated":"2025-02-14T01:02:04Z","snapshot_observed_at":"2026-08-11T19:53:12.706625Z","submitted_at":"2025-01-22T09:27:11Z","title":"EvidenceMap: Learning Evidence Analysis to Unleash the Power of Small Language Models for Biomedical Question Answering","version":4},"reference_index":9,"source":"arxiv_source","source_observed_at":"2026-08-10T16:54:43.896802Z"},"links":{"cited_paper":"/paper/2312.10997","citing_paper":"/paper/2501.12746"},"observation_digest":"sha256:ea22a71d8cc771c0297bccfa7ace4df3566d8b9ccd7a450060000d36a2713106","observation_id":"c371c92f-305d-436f-b98f-38a4e61548b1","resolution":{"observed_at":"2026-08-10T16:54:43.896802Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2402.07630","last_updated":"2024-05-27T04:04:40Z","snapshot_observed_at":"2026-08-11T19:52:53.912972Z","submitted_at":"2024-02-12T13:13:04Z","title":"G-Retriever: Retrieval-Augmented Generation for Textual Graph Understanding and Question Answering","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.07630","snapshot_observed_at":"2026-08-10T16:54:43.901490Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2501.12746","last_updated":"2025-02-14T01:02:04Z","snapshot_observed_at":"2026-08-11T19:53:12.706625Z","submitted_at":"2025-01-22T09:27:11Z","title":"EvidenceMap: Learning Evidence Analysis to Unleash the Power of Small Language Models for Biomedical Question Answering","version":4},"reference_index":10,"source":"arxiv_source","source_observed_at":"2026-08-10T16:54:43.901490Z"},"links":{"cited_paper":"/paper/2402.07630","citing_paper":"/paper/2501.12746"},"observation_digest":"sha256:7a2db2740d3dab48564e5ea0ba7fe5e00c74b6d4405c9cee9c0f949dc3e26e8e","observation_id":"d49cce37-5ef1-4e71-98dc-5aa892317c97","resolution":{"observed_at":"2026-08-10T16:54:43.901490Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2106.09685","last_updated":"2021-10-16T18:40:34Z","snapshot_observed_at":"2026-08-11T08:20:29.798517Z","submitted_at":"2021-06-17T17:37:18Z","title":"LoRA: Low-Rank Adaptation of Large Language Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2106.09685","snapshot_observed_at":"2026-08-10T16:54:43.906187Z","title":null,"venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2501.12746","last_updated":"2025-02-14T01:02:04Z","snapshot_observed_at":"2026-08-11T19:53:12.706625Z","submitted_at":"2025-01-22T09:27:11Z","title":"EvidenceMap: Learning Evidence Analysis to Unleash the Power of Small Language Models for Biomedical Question Answering","version":4},"reference_index":11,"source":"arxiv_source","source_observed_at":"2026-08-10T16:54:43.906187Z"},"links":{"cited_paper":"/paper/2106.09685","citing_paper":"/paper/2501.12746"},"observation_digest":"sha256:dba8c96166ce4e99945bb3a35f73e643bd80a2b7e994c6b32e9e239d393426a9","observation_id":"ad87bc25-5de6-4aff-959d-a0ff1d8c37f7","resolution":{"observed_at":"2026-08-10T16:54:43.906187Z","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":"2026-08-10T16:54:43.910018Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2501.12746","last_updated":"2025-02-14T01:02:04Z","snapshot_observed_at":"2026-08-11T19:53:12.706625Z","submitted_at":"2025-01-22T09:27:11Z","title":"EvidenceMap: Learning Evidence Analysis to Unleash the Power of Small Language Models for Biomedical Question Answering","version":4},"reference_index":12,"source":"arxiv_source","source_observed_at":"2026-08-10T16:54:43.910018Z"},"links":{"citing_paper":"/paper/2501.12746"},"observation_digest":"sha256:9372da993c30ed464fe65dea43043734268412a09255e4f56dc2cc33fa41c828","observation_id":"4dbaca69-2da3-4a69-899c-e6bb73058efd","resolution":{"observed_at":"2026-08-10T16:54:43.910018Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.21276","last_updated":"2024-10-25T17:43:01Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-10-25T17:43:01Z","title":"GPT-4o System Card","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.21276","snapshot_observed_at":"2026-08-10T16:54:43.914458Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2501.12746","last_updated":"2025-02-14T01:02:04Z","snapshot_observed_at":"2026-08-11T19:53:12.706625Z","submitted_at":"2025-01-22T09:27:11Z","title":"EvidenceMap: Learning Evidence Analysis to Unleash the Power of Small Language Models for Biomedical Question Answering","version":4},"reference_index":13,"source":"arxiv_source","source_observed_at":"2026-08-10T16:54:43.914458Z"},"links":{"cited_paper":"/paper/2410.21276","citing_paper":"/paper/2501.12746"},"observation_digest":"sha256:e3992404dc145fffebd44f32a1a8af045d21521ed07b8b8bfbf8add6b591cdfa","observation_id":"7c4b6614-1b4d-4154-b026-987e804e2a62","resolution":{"observed_at":"2026-08-10T16:54:43.914458Z","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":"2026-08-10T16:54:43.918452Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2501.12746","last_updated":"2025-02-14T01:02:04Z","snapshot_observed_at":"2026-08-11T19:53:12.706625Z","submitted_at":"2025-01-22T09:27:11Z","title":"EvidenceMap: Learning Evidence Analysis to Unleash the Power of Small Language Models for Biomedical Question Answering","version":4},"reference_index":14,"source":"arxiv_source","source_observed_at":"2026-08-10T16:54:43.918452Z"},"links":{"citing_paper":"/paper/2501.12746"},"observation_digest":"sha256:1975d12f69e186af7ea801f5e5848eef6ebc4acbb8f89ecc4fdb53808d96f0be","observation_id":"79f49dc1-c1f7-4e15-bd30-f383ddbde3f5","resolution":{"observed_at":"2026-08-10T16:54:43.918452Z","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":"2026-08-10T16:54:43.922016Z","title":null,"venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2501.12746","last_updated":"2025-02-14T01:02:04Z","snapshot_observed_at":"2026-08-11T19:53:12.706625Z","submitted_at":"2025-01-22T09:27:11Z","title":"EvidenceMap: Learning Evidence Analysis to Unleash the Power of Small Language Models for Biomedical Question Answering","version":4},"reference_index":15,"source":"arxiv_source","source_observed_at":"2026-08-10T16:54:43.922016Z"},"links":{"citing_paper":"/paper/2501.12746"},"observation_digest":"sha256:c699978f131d8afd48e18a9bc5f48b7233478b83b5beba0a2ca3ff60fdcbe5a8","observation_id":"7559e491-203a-4ab4-9afe-78c45222f439","resolution":{"observed_at":"2026-08-10T16:54:43.922016Z","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":"2026-08-10T16:54:43.925539Z","title":null,"venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2501.12746","last_updated":"2025-02-14T01:02:04Z","snapshot_observed_at":"2026-08-11T19:53:12.706625Z","submitted_at":"2025-01-22T09:27:11Z","title":"EvidenceMap: Learning Evidence Analysis to Unleash the Power of Small Language Models for Biomedical Question Answering","version":4},"reference_index":16,"source":"arxiv_source","source_observed_at":"2026-08-10T16:54:43.925539Z"},"links":{"citing_paper":"/paper/2501.12746"},"observation_digest":"sha256:e4d0548958a8a81c19409b492889f07d7b6815abe7708dbadda5f52eee28d91b","observation_id":"9c25abe2-712f-4d44-a19a-8156ed509165","resolution":{"observed_at":"2026-08-10T16:54:43.925539Z","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":"2026-08-10T16:54:43.928874Z","title":null,"venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2501.12746","last_updated":"2025-02-14T01:02:04Z","snapshot_observed_at":"2026-08-11T19:53:12.706625Z","submitted_at":"2025-01-22T09:27:11Z","title":"EvidenceMap: Learning Evidence Analysis to Unleash the Power of Small Language Models for Biomedical Question Answering","version":4},"reference_index":17,"source":"arxiv_source","source_observed_at":"2026-08-10T16:54:43.928874Z"},"links":{"citing_paper":"/paper/2501.12746"},"observation_digest":"sha256:7cb49d9ac2cea711ce7a3e1ccbb64bfb8161580686dc6a741a88f8043225e338","observation_id":"658f35ff-2eb8-4031-8dce-522b95ed29ad","resolution":{"observed_at":"2026-08-10T16:54:43.928874Z","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":"2026-08-10T16:54:44.501986Z","title":null,"venue":null,"work_id":"33807bb0-bf7f-47c0-a26e-42364159d47a","year":2023},"citing_paper":{"arxiv_id":"2501.12746","last_updated":"2025-02-14T01:02:04Z","snapshot_observed_at":"2026-08-11T19:53:12.706625Z","submitted_at":"2025-01-22T09:27:11Z","title":"EvidenceMap: Learning Evidence Analysis to Unleash the Power of Small Language Models for Biomedical Question Answering","version":4},"reference_index":18,"source":"arxiv_source","source_observed_at":"2026-08-10T16:54:43.932678Z"},"links":{"citing_paper":"/paper/2501.12746"},"observation_digest":"sha256:b819e53880f8de1167a90e3dd01e1f6237eb04d805293bb11f20fd02fd08a08b","observation_id":"1cc8c146-d970-4e48-a02c-6ba355531141","resolution":{"observed_at":"2026-08-10T16:54:44.507017Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-10T16:54:43.937006Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2501.12746","last_updated":"2025-02-14T01:02:04Z","snapshot_observed_at":"2026-08-11T19:53:12.706625Z","submitted_at":"2025-01-22T09:27:11Z","title":"EvidenceMap: Learning Evidence Analysis to Unleash the Power of Small Language Models for Biomedical Question Answering","version":4},"reference_index":19,"source":"arxiv_source","source_observed_at":"2026-08-10T16:54:43.937006Z"},"links":{"citing_paper":"/paper/2501.12746"},"observation_digest":"sha256:fb7666b5c8782dccc6615a811246f2d848d1d5012908f617792c00bfee49cb64","observation_id":"32bd96d7-39ae-49f0-8821-0da2bf98338e","resolution":{"observed_at":"2026-08-10T16:54:43.937006Z","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":"2026-08-10T16:54:43.941012Z","title":null,"venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2501.12746","last_updated":"2025-02-14T01:02:04Z","snapshot_observed_at":"2026-08-11T19:53:12.706625Z","submitted_at":"2025-01-22T09:27:11Z","title":"EvidenceMap: Learning Evidence Analysis to Unleash the Power of Small Language Models for Biomedical Question Answering","version":4},"reference_index":20,"source":"arxiv_source","source_observed_at":"2026-08-10T16:54:43.941012Z"},"links":{"citing_paper":"/paper/2501.12746"},"observation_digest":"sha256:007239f05055f8f5749926b61b08d09ddd672f5c4702b8d548cf1bea1cad5c7b","observation_id":"c926c67c-9483-4b10-b4b2-dc4f33216dd8","resolution":{"observed_at":"2026-08-10T16:54:43.941012Z","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":"2026-08-10T16:54:44.481893Z","title":"u ttler, Mike Lewis, Wen-tau Yih, Tim Rockt \\","venue":null,"work_id":"4f2d002e-e7e9-4cea-a4dd-6c1abc9f4146","year":2020},"citing_paper":{"arxiv_id":"2501.12746","last_updated":"2025-02-14T01:02:04Z","snapshot_observed_at":"2026-08-11T19:53:12.706625Z","submitted_at":"2025-01-22T09:27:11Z","title":"EvidenceMap: Learning Evidence Analysis to Unleash the Power of Small Language Models for Biomedical Question Answering","version":4},"reference_index":21,"source":"arxiv_source","source_observed_at":"2026-08-10T16:54:43.944858Z"},"links":{"citing_paper":"/paper/2501.12746"},"observation_digest":"sha256:72192e5d1730520f0d448375a68ab4c88ee39412ca2c577fd926b7cdb6bb4461","observation_id":"fc9ec7dc-3a71-4a69-8720-2b95930f22e5","resolution":{"observed_at":"2026-08-10T16:54:44.486620Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-10T16:54:43.948832Z","title":null,"venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2501.12746","last_updated":"2025-02-14T01:02:04Z","snapshot_observed_at":"2026-08-11T19:53:12.706625Z","submitted_at":"2025-01-22T09:27:11Z","title":"EvidenceMap: Learning Evidence Analysis to Unleash the Power of Small Language Models for Biomedical Question Answering","version":4},"reference_index":22,"source":"arxiv_source","source_observed_at":"2026-08-10T16:54:43.948832Z"},"links":{"citing_paper":"/paper/2501.12746"},"observation_digest":"sha256:4465aa44fe38f88e6ffaa0cd8c4010dba8e28558b0df7a6a034cc364a787cf5a","observation_id":"e6d744aa-20a4-4753-83da-3fbedee81df1","resolution":{"observed_at":"2026-08-10T16:54:43.948832Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2305.20050","last_updated":"2023-05-31T17:24:00Z","snapshot_observed_at":"2026-08-11T17:22:43.545531Z","submitted_at":"2023-05-31T17:24:00Z","title":"Let's Verify Step by Step","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2305.20050","snapshot_observed_at":"2026-08-10T16:54:43.952956Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2501.12746","last_updated":"2025-02-14T01:02:04Z","snapshot_observed_at":"2026-08-11T19:53:12.706625Z","submitted_at":"2025-01-22T09:27:11Z","title":"EvidenceMap: Learning Evidence Analysis to Unleash the Power of Small Language Models for Biomedical Question Answering","version":4},"reference_index":23,"source":"arxiv_source","source_observed_at":"2026-08-10T16:54:43.952956Z"},"links":{"cited_paper":"/paper/2305.20050","citing_paper":"/paper/2501.12746"},"observation_digest":"sha256:441fa3719a5209ee9ff3064bf5ef4ea80eb691a1c62459de7b66f46ba2743621","observation_id":"8739db36-3dd7-4097-90ba-b30270eb51e5","resolution":{"observed_at":"2026-08-10T16:54:43.952956Z","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":"2026-08-10T16:54:43.956905Z","title":null,"venue":null,"work_id":null,"year":2004},"citing_paper":{"arxiv_id":"2501.12746","last_updated":"2025-02-14T01:02:04Z","snapshot_observed_at":"2026-08-11T19:53:12.706625Z","submitted_at":"2025-01-22T09:27:11Z","title":"EvidenceMap: Learning Evidence Analysis to Unleash the Power of Small Language Models for Biomedical Question Answering","version":4},"reference_index":24,"source":"arxiv_source","source_observed_at":"2026-08-10T16:54:43.956905Z"},"links":{"citing_paper":"/paper/2501.12746"},"observation_digest":"sha256:b1aafe553363514fe93bc4322459dadd4872752fe55e2c0026a64080fba78cb7","observation_id":"2478198d-d8b9-410d-8a7d-516dd43ce51f","resolution":{"observed_at":"2026-08-10T16:54:43.956905Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2310.01352","last_updated":"2024-05-06T07:50:35Z","snapshot_observed_at":"2026-08-10T12:05:58.040897Z","submitted_at":"2023-10-02T17:16:26Z","title":"RA-DIT: Retrieval-Augmented Dual Instruction Tuning","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.01352","snapshot_observed_at":"2026-08-10T16:54:43.960983Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2501.12746","last_updated":"2025-02-14T01:02:04Z","snapshot_observed_at":"2026-08-11T19:53:12.706625Z","submitted_at":"2025-01-22T09:27:11Z","title":"EvidenceMap: Learning Evidence Analysis to Unleash the Power of Small Language Models for Biomedical Question Answering","version":4},"reference_index":25,"source":"arxiv_source","source_observed_at":"2026-08-10T16:54:43.960983Z"},"links":{"cited_paper":"/paper/2310.01352","citing_paper":"/paper/2501.12746"},"observation_digest":"sha256:8509860e3f6e634c2cbbbe707ca1dc4c49eb7f6714391589829f0ef387e2972a","observation_id":"1e87e5fc-16c9-447f-8b12-7fa812900c5a","resolution":{"observed_at":"2026-08-10T16:54:43.960983Z","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":"2026-08-10T16:54:44.461738Z","title":null,"venue":null,"work_id":"d523c55d-3f6b-4a0f-a91c-3517aa5389a0","year":2024},"citing_paper":{"arxiv_id":"2501.12746","last_updated":"2025-02-14T01:02:04Z","snapshot_observed_at":"2026-08-11T19:53:12.706625Z","submitted_at":"2025-01-22T09:27:11Z","title":"EvidenceMap: Learning Evidence Analysis to Unleash the Power of Small Language Models for Biomedical Question Answering","version":4},"reference_index":26,"source":"arxiv_source","source_observed_at":"2026-08-10T16:54:43.965442Z"},"links":{"citing_paper":"/paper/2501.12746"},"observation_digest":"sha256:c28916cbbf85f6fe552fe0a2de025a0e916edc23489a6ed61de3f8699f7f8ebc","observation_id":"856c6e48-51f1-43d9-81fc-e4fbeb602284","resolution":{"observed_at":"2026-08-10T16:54:44.466036Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-10T16:54:44.448738Z","title":null,"venue":null,"work_id":"78d2a366-4f81-4805-9cc7-35e827feeb37","year":2024},"citing_paper":{"arxiv_id":"2501.12746","last_updated":"2025-02-14T01:02:04Z","snapshot_observed_at":"2026-08-11T19:53:12.706625Z","submitted_at":"2025-01-22T09:27:11Z","title":"EvidenceMap: Learning Evidence Analysis to Unleash the Power of Small Language Models for Biomedical Question Answering","version":4},"reference_index":27,"source":"arxiv_source","source_observed_at":"2026-08-10T16:54:43.969924Z"},"links":{"citing_paper":"/paper/2501.12746"},"observation_digest":"sha256:38b5873ff8ccef4a6f6c69dc6e62c319795580ee409ef01612e7f776c267c1a8","observation_id":"954ee083-0200-4a6f-b4cc-6b2e184ef82b","resolution":{"observed_at":"2026-08-10T16:54:44.452530Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-10T16:54:43.974822Z","title":null,"venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2501.12746","last_updated":"2025-02-14T01:02:04Z","snapshot_observed_at":"2026-08-11T19:53:12.706625Z","submitted_at":"2025-01-22T09:27:11Z","title":"EvidenceMap: Learning Evidence Analysis to Unleash the Power of Small Language Models for Biomedical Question Answering","version":4},"reference_index":28,"source":"arxiv_source","source_observed_at":"2026-08-10T16:54:43.974822Z"},"links":{"citing_paper":"/paper/2501.12746"},"observation_digest":"sha256:75b2f98e31e412deb0e38f70ed944d3ea050f7a07347592309a3596bb8702295","observation_id":"0f1715bd-48c5-417e-a36d-cedbadf886eb","resolution":{"observed_at":"2026-08-10T16:54:43.974822Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1910.01108","last_updated":"2020-03-01T02:57:50Z","snapshot_observed_at":"2026-08-07T19:07:36.327251Z","submitted_at":"2019-10-02T17:56:28Z","title":"DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighter","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1910.01108","snapshot_observed_at":"2026-08-10T16:54:43.979479Z","title":null,"venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2501.12746","last_updated":"2025-02-14T01:02:04Z","snapshot_observed_at":"2026-08-11T19:53:12.706625Z","submitted_at":"2025-01-22T09:27:11Z","title":"EvidenceMap: Learning Evidence Analysis to Unleash the Power of Small Language Models for Biomedical Question Answering","version":4},"reference_index":29,"source":"arxiv_source","source_observed_at":"2026-08-10T16:54:43.979479Z"},"links":{"cited_paper":"/paper/1910.01108","citing_paper":"/paper/2501.12746"},"observation_digest":"sha256:9d435250ac339222704fd69942c5834fcb31f919b7743e6c3329e779be183893","observation_id":"86ca8d24-5aa0-4eba-9b55-7b1ce9998d73","resolution":{"observed_at":"2026-08-10T16:54:43.979479Z","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":"2026-08-10T16:54:43.983910Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2501.12746","last_updated":"2025-02-14T01:02:04Z","snapshot_observed_at":"2026-08-11T19:53:12.706625Z","submitted_at":"2025-01-22T09:27:11Z","title":"EvidenceMap: Learning Evidence Analysis to Unleash the Power of Small Language Models for Biomedical Question Answering","version":4},"reference_index":30,"source":"arxiv_source","source_observed_at":"2026-08-10T16:54:43.983910Z"},"links":{"citing_paper":"/paper/2501.12746"},"observation_digest":"sha256:4bbff2f12178bb5e8b277a076c009761ae8538dccf3abee6cf4d3e09defb9bba","observation_id":"c06d0c65-c9df-4871-a962-7122378cc023","resolution":{"observed_at":"2026-08-10T16:54:43.983910Z","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":"2026-08-10T16:54:43.988299Z","title":null,"venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2501.12746","last_updated":"2025-02-14T01:02:04Z","snapshot_observed_at":"2026-08-11T19:53:12.706625Z","submitted_at":"2025-01-22T09:27:11Z","title":"EvidenceMap: Learning Evidence Analysis to Unleash the Power of Small Language Models for Biomedical Question Answering","version":4},"reference_index":31,"source":"arxiv_source","source_observed_at":"2026-08-10T16:54:43.988299Z"},"links":{"citing_paper":"/paper/2501.12746"},"observation_digest":"sha256:9f4fa6811534fbb05b72846343c1578bb753254873144bd51c81092287af90a5","observation_id":"67964d83-7da9-4705-8239-a20075e198f8","resolution":{"observed_at":"2026-08-10T16:54:43.988299Z","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":"2026-08-10T16:54:43.992490Z","title":"Smith, Daniel Khashabi, and Hannaneh Hajishirzi","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2501.12746","last_updated":"2025-02-14T01:02:04Z","snapshot_observed_at":"2026-08-11T19:53:12.706625Z","submitted_at":"2025-01-22T09:27:11Z","title":"EvidenceMap: Learning Evidence Analysis to Unleash the Power of Small Language Models for Biomedical Question Answering","version":4},"reference_index":32,"source":"arxiv_source","source_observed_at":"2026-08-10T16:54:43.992490Z"},"links":{"citing_paper":"/paper/2501.12746"},"observation_digest":"sha256:ae09bca1c2a36126086b945935453a64097bd7a30ef88c7390d9393e55ecb063","observation_id":"b48553fe-447e-4d32-a63e-270557898a67","resolution":{"observed_at":"2026-08-10T16:54:43.992490Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2403.05313","last_updated":"2024-03-08T13:42:19Z","snapshot_observed_at":"2026-08-11T12:59:40.041297Z","submitted_at":"2024-03-08T13:42:19Z","title":"RAT: Retrieval Augmented Thoughts Elicit Context-Aware Reasoning in Long-Horizon Generation","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2403.05313","snapshot_observed_at":"2026-08-10T16:54:43.996417Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2501.12746","last_updated":"2025-02-14T01:02:04Z","snapshot_observed_at":"2026-08-11T19:53:12.706625Z","submitted_at":"2025-01-22T09:27:11Z","title":"EvidenceMap: Learning Evidence Analysis to Unleash the Power of Small Language Models for Biomedical Question Answering","version":4},"reference_index":33,"source":"arxiv_source","source_observed_at":"2026-08-10T16:54:43.996417Z"},"links":{"cited_paper":"/paper/2403.05313","citing_paper":"/paper/2501.12746"},"observation_digest":"sha256:f2a12579027a61672c16f1daf29db3570a32a73b55feb4b3aa731fdce04db59f","observation_id":"5956505d-36a8-47f5-8a8b-232a2076a9c0","resolution":{"observed_at":"2026-08-10T16:54:43.996417Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2412.13663","last_updated":"2024-12-19T06:32:26Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-12-18T09:39:44Z","title":"Smarter, Better, Faster, Longer: A Modern Bidirectional Encoder for Fast, Memory Efficient, and Long Context Finetuning and Inference","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2412.13663","snapshot_observed_at":"2026-08-10T16:54:44.000860Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2501.12746","last_updated":"2025-02-14T01:02:04Z","snapshot_observed_at":"2026-08-11T19:53:12.706625Z","submitted_at":"2025-01-22T09:27:11Z","title":"EvidenceMap: Learning Evidence Analysis to Unleash the Power of Small Language Models for Biomedical Question Answering","version":4},"reference_index":34,"source":"arxiv_source","source_observed_at":"2026-08-10T16:54:44.000860Z"},"links":{"cited_paper":"/paper/2412.13663","citing_paper":"/paper/2501.12746"},"observation_digest":"sha256:d08bf68dcef3c201bf68ee6f511fe05dbc8060481c936c325b3b1313511b43bd","observation_id":"ad30e73a-ec5e-4280-b26b-66fa73a1ead1","resolution":{"observed_at":"2026-08-10T16:54:44.000860Z","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":"2026-08-10T16:54:44.005567Z","title":null,"venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2501.12746","last_updated":"2025-02-14T01:02:04Z","snapshot_observed_at":"2026-08-11T19:53:12.706625Z","submitted_at":"2025-01-22T09:27:11Z","title":"EvidenceMap: Learning Evidence Analysis to Unleash the Power of Small Language Models for Biomedical Question Answering","version":4},"reference_index":35,"source":"arxiv_source","source_observed_at":"2026-08-10T16:54:44.005567Z"},"links":{"citing_paper":"/paper/2501.12746"},"observation_digest":"sha256:294d62e0d2e0ebe4f3865b6dd0810423b2687fb8a86580b7af6bbee779eb0439","observation_id":"e4dd8410-ccf6-473a-9fc3-e33dc00d21fe","resolution":{"observed_at":"2026-08-10T16:54:44.005567Z","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":"2026-08-10T16:54:44.402038Z","title":null,"venue":null,"work_id":"f186bd46-f6f2-434c-ad9e-b918cbcb3e33","year":2022},"citing_paper":{"arxiv_id":"2501.12746","last_updated":"2025-02-14T01:02:04Z","snapshot_observed_at":"2026-08-11T19:53:12.706625Z","submitted_at":"2025-01-22T09:27:11Z","title":"EvidenceMap: Learning Evidence Analysis to Unleash the Power of Small Language Models for Biomedical Question Answering","version":4},"reference_index":36,"source":"arxiv_source","source_observed_at":"2026-08-10T16:54:44.010303Z"},"links":{"citing_paper":"/paper/2501.12746"},"observation_digest":"sha256:6c96dc72fc7caa9ff429115472c57540ccefc5a5e3bf1d521b5f023d5d206f02","observation_id":"95c4f731-9566-4113-84a6-99f359f5f112","resolution":{"observed_at":"2026-08-10T16:54:44.407021Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.15115","last_updated":"2025-01-03T02:18:21Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-12-19T17:56:09Z","title":"Qwen2.5 Technical Report","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2412.15115","snapshot_observed_at":"2026-08-10T16:54:44.014498Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2501.12746","last_updated":"2025-02-14T01:02:04Z","snapshot_observed_at":"2026-08-11T19:53:12.706625Z","submitted_at":"2025-01-22T09:27:11Z","title":"EvidenceMap: Learning Evidence Analysis to Unleash the Power of Small Language Models for Biomedical Question Answering","version":4},"reference_index":37,"source":"arxiv_source","source_observed_at":"2026-08-10T16:54:44.014498Z"},"links":{"cited_paper":"/paper/2412.15115","citing_paper":"/paper/2501.12746"},"observation_digest":"sha256:683fc29a6494a1c8b2b98ddd7f4461aac9ebe9828fbb43cc651077c0e50450c7","observation_id":"8e8571fc-2855-4b8d-8ee9-58fd6a914df1","resolution":{"observed_at":"2026-08-10T16:54:44.014498Z","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":"10.18653/v1/2023.acl-long.25","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T16:54:44.063935Z","title":null,"venue":null,"work_id":"94084c42-fc87-438a-8d7e-00330d97ae50","year":2023},"citing_paper":{"arxiv_id":"2501.12746","last_updated":"2025-02-14T01:02:04Z","snapshot_observed_at":"2026-08-11T19:53:12.706625Z","submitted_at":"2025-01-22T09:27:11Z","title":"EvidenceMap: Learning Evidence Analysis to Unleash the Power of Small Language Models for Biomedical Question Answering","version":4},"reference_index":38,"source":"arxiv_source","source_observed_at":"2026-08-10T16:54:44.018689Z"},"links":{"citing_paper":"/paper/2501.12746"},"observation_digest":"sha256:bb69ebd496e1dc539b885a5739e79cdbcd4fe89e84f198f328c71b03ae23ea9f","observation_id":"10e82dfd-d850-4418-a9a4-41a599d8715a","resolution":{"observed_at":"2026-08-10T16:54:44.070343Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+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":"2026-08-10T16:54:44.022645Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2501.12746","last_updated":"2025-02-14T01:02:04Z","snapshot_observed_at":"2026-08-11T19:53:12.706625Z","submitted_at":"2025-01-22T09:27:11Z","title":"EvidenceMap: Learning Evidence Analysis to Unleash the Power of Small Language Models for Biomedical Question Answering","version":4},"reference_index":39,"source":"arxiv_source","source_observed_at":"2026-08-10T16:54:44.022645Z"},"links":{"citing_paper":"/paper/2501.12746"},"observation_digest":"sha256:c95a1837467f7e6206db58112c9f0838d9f57c3e6da864e7deeab9fff0c899e5","observation_id":"eccce7e9-96c3-4598-8966-95ef3f6fe9cd","resolution":{"observed_at":"2026-08-10T16:54:44.022645Z","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":"2026-08-10T16:54:44.377989Z","title":null,"venue":null,"work_id":"134bcf85-eef5-40a5-a4d1-86c9b667f8f6","year":2024},"citing_paper":{"arxiv_id":"2501.12746","last_updated":"2025-02-14T01:02:04Z","snapshot_observed_at":"2026-08-11T19:53:12.706625Z","submitted_at":"2025-01-22T09:27:11Z","title":"EvidenceMap: Learning Evidence Analysis to Unleash the Power of Small Language Models for Biomedical Question Answering","version":4},"reference_index":40,"source":"arxiv_source","source_observed_at":"2026-08-10T16:54:44.026626Z"},"links":{"citing_paper":"/paper/2501.12746"},"observation_digest":"sha256:b4d7fe821bf8930c5042e248ca7057f9d132874519c679b5f46bfd5c853837a9","observation_id":"afa2dcf0-dc01-4119-be98-d0b31300e5b1","resolution":{"observed_at":"2026-08-10T16:54:44.382630Z","resolver_source":"raw_fallback","status":"unresolved"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1904.09675","last_updated":"2020-02-24T18:59:28Z","snapshot_observed_at":"2026-07-29T15:42:51.774083Z","submitted_at":"2019-04-21T23:08:53Z","title":"BERTScore: Evaluating Text Generation with BERT","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1904.09675","snapshot_observed_at":"2026-08-10T16:54:44.030480Z","title":null,"venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2501.12746","last_updated":"2025-02-14T01:02:04Z","snapshot_observed_at":"2026-08-11T19:53:12.706625Z","submitted_at":"2025-01-22T09:27:11Z","title":"EvidenceMap: Learning Evidence Analysis to Unleash the Power of Small Language Models for Biomedical Question Answering","version":4},"reference_index":41,"source":"arxiv_source","source_observed_at":"2026-08-10T16:54:44.030480Z"},"links":{"cited_paper":"/paper/1904.09675","citing_paper":"/paper/2501.12746"},"observation_digest":"sha256:32e8e8a45f095ac6d4a010b9f9aededa486822343200e0feba617ff0d4c68a30","observation_id":"455de7e0-7c67-40f5-89ff-aa64126645da","resolution":{"observed_at":"2026-08-10T16:54:44.030480Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2501.12746","last_updated":"2025-02-14T01:02:04Z","latest_version":4,"primary_category":"cs.CL","snapshot_observed_at":"2026-08-11T19:53:12.706625Z","submitted_at":"2025-01-22T09:27:11Z","title":"EvidenceMap: Learning Evidence Analysis to Unleash the Power of Small Language Models for Biomedical Question Answering"},"reference_resolution":{"displayed":41,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":39,"verified_exact":1,"verified_fuzzy":1},"total_outbound_references":41},"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":"2026-08-11T06:34:44.6726+00:00","source":"crossref"},{"observed_at":"2026-08-11T06:34:36.301508+00:00","source":"retraction_watch"}],"thesis":"As of 12 August 2026, this Paper Citation Record lists 41 of 41 outbound references and 0 inbound Pith citation observations for arXiv:2501.12746."}