{"as_of":"2026-08-07T20:57:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:e5fad67960df61527a77fe7269037a20f8934df4f25220f1ae37351be8ab8e64","coverage":[{"denominator":300,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":100,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-06T20:45:12.227761Z","state":"measured"},{"denominator":133,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":133,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-07T06:34:17.273281+00:00","state":"measured"},{"denominator":33,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":33,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-06T17:49:34.746783Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":1,"source":"arxiv_reference","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":"arxiv_reference"}],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2507.01903","last_updated":"2025-08-05T16:19:40Z","snapshot_observed_at":"2026-08-07T12:18:28.218519Z","submitted_at":"2025-07-02T17:19:20Z","title":"AI4Research: A Survey of Artificial Intelligence for Scientific Research","version":2},"cited_work":{"arxiv_id":"2507.01903","doi":"10.48550/arxiv.2507.01903","metadata_source":"arxiv_reference","pith_arxiv_id":"2507.01903","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"AI4Research","venue":"ArXiv.org","work_id":"8434d9d4-cce5-4158-b4f0-acc351e5bb4c","year":2024},"citing_paper":{"arxiv_id":"2503.09567","last_updated":"2025-07-18T15:57:54Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-03-12T17:35:03Z","title":"Towards Reasoning Era: A Survey of Long Chain-of-Thought for Reasoning Large Language Models","version":5},"reference_index":97,"source":"pdf_text","source_observed_at":"2026-05-12T08:40:40.910461Z"},"links":{"cited_paper":"/paper/2507.01903","citing_paper":"/paper/2503.09567"},"observation_digest":"sha256:50efb070fbc0fc1a710e006d3f5c39907dfb0ac3ed71a50620454f11223140a3","observation_id":"054a046c-2baf-4761-a188-f2d9fc3f3339","resolution":{"observed_at":"2026-05-12T08:40:41.864505Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-05-25T19:23:19.926431+00:00","source":"crossref_status_cache"},{"observed_at":"2026-05-25T19:23:19.926431+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2507.01903","last_updated":"2025-08-05T16:19:40Z","snapshot_observed_at":"2026-08-07T12:18:28.218519Z","submitted_at":"2025-07-02T17:19:20Z","title":"AI4Research: A Survey of Artificial Intelligence for Scientific Research","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2507.01903","snapshot_observed_at":"2026-08-06T17:49:34.746783Z","title":null,"venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2507.09876","last_updated":"2025-07-14T03:21:13Z","snapshot_observed_at":"2026-08-06T17:42:42.583231Z","submitted_at":"2025-07-14T03:21:13Z","title":"ViTCoT: Video-Text Interleaved Chain-of-Thought for Boosting Video Understanding in Large Language Models","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-06T17:49:34.746783Z"},"links":{"cited_paper":"/paper/2507.01903","citing_paper":"/paper/2507.09876"},"observation_digest":"sha256:24f2c2678d77dad7339672fed2888304ec79ad659637af0573d31fea8ba828ae","observation_id":"6b51a282-7bef-46aa-bf45-3d01fdc5038b","resolution":{"observed_at":"2026-08-06T17:49:34.746783Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2507.01903","last_updated":"2025-08-05T16:19:40Z","snapshot_observed_at":"2026-08-07T12:18:28.218519Z","submitted_at":"2025-07-02T17:19:20Z","title":"AI4Research: A Survey of Artificial Intelligence for Scientific Research","version":2},"cited_work":{"arxiv_id":"2507.01903","doi":"10.48550/arxiv.2507.01903","metadata_source":"arxiv_reference","pith_arxiv_id":"2507.01903","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"AI4Research","venue":"ArXiv.org","work_id":"8434d9d4-cce5-4158-b4f0-acc351e5bb4c","year":2024},"citing_paper":{"arxiv_id":"2507.11810","last_updated":"2026-05-11T19:19:50Z","snapshot_observed_at":"2026-07-06T21:57:50.776977Z","submitted_at":"2025-07-16T00:11:01Z","title":"Evolving Roles of LLMs in Scientific Innovation: Assistant, Collaborator, Scientist, and Evaluator","version":2},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-05-19T05:15:49.513101Z"},"links":{"cited_paper":"/paper/2507.01903","citing_paper":"/paper/2507.11810"},"observation_digest":"sha256:83cb22f7e60976e4089b0e7517f842b70f1b17ffaed29c4e947700654f6dc7df","observation_id":"9de6e563-501c-4a0a-8d3e-fada0ddf1a63","resolution":{"observed_at":"2026-05-19T05:17:06.126504Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-05-25T19:23:19.926431+00:00","source":"crossref_status_cache"},{"observed_at":"2026-05-25T19:23:19.926431+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2507.01903","last_updated":"2025-08-05T16:19:40Z","snapshot_observed_at":"2026-08-07T12:18:28.218519Z","submitted_at":"2025-07-02T17:19:20Z","title":"AI4Research: A Survey of Artificial Intelligence for Scientific Research","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2507.01903","snapshot_observed_at":"2026-08-06T16:30:30.888470Z","title":null,"venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2507.13300","last_updated":"2025-07-17T17:09:22Z","snapshot_observed_at":"2026-08-07T12:19:08.248754Z","submitted_at":"2025-07-17T17:09:22Z","title":"AbGen: Evaluating Large Language Models in Ablation Study Design and Evaluation for Scientific Research","version":1},"reference_index":7,"source":"arxiv_source","source_observed_at":"2026-08-06T16:30:30.888470Z"},"links":{"cited_paper":"/paper/2507.01903","citing_paper":"/paper/2507.13300"},"observation_digest":"sha256:aeb9cd4efdbb0027ce86a4cc61c3c9ede4f9e01fbadba976e1ef014043dc1e27","observation_id":"4300e2b8-afb0-47d2-9086-758216bafeca","resolution":{"observed_at":"2026-08-06T16:30:30.888470Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2507.01903","last_updated":"2025-08-05T16:19:40Z","snapshot_observed_at":"2026-08-07T12:18:28.218519Z","submitted_at":"2025-07-02T17:19:20Z","title":"AI4Research: A Survey of Artificial Intelligence for Scientific Research","version":2},"cited_work":{"arxiv_id":"2507.01903","doi":"10.48550/arxiv.2507.01903","metadata_source":"arxiv_reference","pith_arxiv_id":"2507.01903","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"AI4Research","venue":"ArXiv.org","work_id":"8434d9d4-cce5-4158-b4f0-acc351e5bb4c","year":2024},"citing_paper":{"arxiv_id":"2507.13334","last_updated":"2025-07-21T17:48:18Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-07-17T17:50:36Z","title":"A Survey of Context Engineering for Large Language Models","version":2},"reference_index":152,"source":"pdf_text","source_observed_at":"2026-05-13T20:58:45.060041Z"},"links":{"cited_paper":"/paper/2507.01903","citing_paper":"/paper/2507.13334"},"observation_digest":"sha256:9c4aa7998aaddcec3925c76fb58a4c33c3d7b3565bad0b0bbb0a70b441d28916","observation_id":"fab39a64-f1c8-472e-90a5-707a1170ea17","resolution":{"observed_at":"2026-05-13T20:58:45.346428Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-05-25T19:23:19.926431+00:00","source":"crossref_status_cache"},{"observed_at":"2026-05-25T19:23:19.926431+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2507.01903","last_updated":"2025-08-05T16:19:40Z","snapshot_observed_at":"2026-08-07T12:18:28.218519Z","submitted_at":"2025-07-02T17:19:20Z","title":"AI4Research: A Survey of Artificial Intelligence for Scientific Research","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2507.01903","snapshot_observed_at":"2026-08-06T15:24:19.362052Z","title":null,"venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2507.16075","last_updated":"2025-07-21T21:23:21Z","snapshot_observed_at":"2026-08-07T12:20:24.237770Z","submitted_at":"2025-07-21T21:23:21Z","title":"Deep Researcher with Test-Time Diffusion","version":1},"reference_index":4,"source":"arxiv_source","source_observed_at":"2026-08-06T15:24:19.362052Z"},"links":{"cited_paper":"/paper/2507.01903","citing_paper":"/paper/2507.16075"},"observation_digest":"sha256:c51498ae219520d4453c2d42cc0a82500dc935eb98c30b27373bab897d9b166b","observation_id":"f039b748-36d9-45d6-8fc8-40b4c2bf4f2b","resolution":{"observed_at":"2026-08-06T15:24:19.362052Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2507.01903","last_updated":"2025-08-05T16:19:40Z","snapshot_observed_at":"2026-08-07T12:18:28.218519Z","submitted_at":"2025-07-02T17:19:20Z","title":"AI4Research: A Survey of Artificial Intelligence for Scientific Research","version":2},"cited_work":{"arxiv_id":"2507.01903","doi":"10.48550/arxiv.2507.01903","metadata_source":"arxiv_reference","pith_arxiv_id":"2507.01903","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"AI4Research","venue":"ArXiv.org","work_id":"8434d9d4-cce5-4158-b4f0-acc351e5bb4c","year":2024},"citing_paper":{"arxiv_id":"2508.11548","last_updated":"2026-04-07T07:06:44Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-08-15T15:50:20Z","title":"Copyright Protection for Large Language Models: A Survey of Methods, Challenges, and Trends","version":2},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-05-18T22:45:31.935618Z"},"links":{"cited_paper":"/paper/2507.01903","citing_paper":"/paper/2508.11548"},"observation_digest":"sha256:2e49deb94c03a30c9ad6c760a062cc3b2a5e1a3721cab13ab610b577a628d61f","observation_id":"896271ea-f7ff-46f2-8bde-7cd6f683cf81","resolution":{"observed_at":"2026-05-18T22:46:53.257408Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-05-25T19:23:19.926431+00:00","source":"crossref_status_cache"},{"observed_at":"2026-05-25T19:23:19.926431+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2507.01903","last_updated":"2025-08-05T16:19:40Z","snapshot_observed_at":"2026-08-07T12:18:28.218519Z","submitted_at":"2025-07-02T17:19:20Z","title":"AI4Research: A Survey of Artificial Intelligence for Scientific Research","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2507.01903","snapshot_observed_at":"2026-08-02T18:14:52.495524Z","title":"Ai4research: A survey of artificial intelligence for scientific research, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2603.14473","last_updated":"2026-07-15T10:22:14Z","snapshot_observed_at":"2026-08-05T20:09:51.962104Z","submitted_at":"2026-03-15T16:31:51Z","title":"AI Can Learn Scientific Taste","version":2},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-02T18:14:52.495524Z"},"links":{"cited_paper":"/paper/2507.01903","citing_paper":"/paper/2603.14473"},"observation_digest":"sha256:000b85c5e165b4ce9ec8bbfc4199414abb19f26d8368d6160c07be2650f1c896","observation_id":"15a31f7b-fee0-46f2-84ba-1cae8434da87","resolution":{"observed_at":"2026-08-02T18:14:52.495524Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2507.01903","last_updated":"2025-08-05T16:19:40Z","snapshot_observed_at":"2026-08-07T12:18:28.218519Z","submitted_at":"2025-07-02T17:19:20Z","title":"AI4Research: A Survey of Artificial Intelligence for Scientific Research","version":2},"cited_work":{"arxiv_id":"2507.01903","doi":"10.48550/arxiv.2507.01903","metadata_source":"arxiv_reference","pith_arxiv_id":"2507.01903","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"AI4Research","venue":"ArXiv.org","work_id":"8434d9d4-cce5-4158-b4f0-acc351e5bb4c","year":2024},"citing_paper":{"arxiv_id":"2603.27771","last_updated":"2026-04-04T07:45:49Z","snapshot_observed_at":"2026-07-06T22:51:00.579062Z","submitted_at":"2026-03-29T17:10:28Z","title":"Emergent Social Intelligence Risks in Generative Multi-Agent Systems","version":2},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-05-14T21:45:04.625084Z"},"links":{"cited_paper":"/paper/2507.01903","citing_paper":"/paper/2603.27771"},"observation_digest":"sha256:4e85af57b52b5597588108311b6cb5bac042c315a3a9f00d280028a4767ec337","observation_id":"3472a24a-cbc3-423b-96f9-c71162dedcb3","resolution":{"observed_at":"2026-05-14T21:48:00.823871Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-05-25T19:23:19.926431+00:00","source":"crossref_status_cache"},{"observed_at":"2026-05-25T19:23:19.926431+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2507.01903","last_updated":"2025-08-05T16:19:40Z","snapshot_observed_at":"2026-08-07T12:18:28.218519Z","submitted_at":"2025-07-02T17:19:20Z","title":"AI4Research: A Survey of Artificial Intelligence for Scientific Research","version":2},"cited_work":{"arxiv_id":"2507.01903","doi":"10.48550/arxiv.2507.01903","metadata_source":"arxiv_reference","pith_arxiv_id":"2507.01903","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"AI4Research","venue":"ArXiv.org","work_id":"8434d9d4-cce5-4158-b4f0-acc351e5bb4c","year":2024},"citing_paper":{"arxiv_id":"2604.16929","last_updated":"2026-04-18T09:26:52Z","snapshot_observed_at":"2026-07-06T23:04:10.324443Z","submitted_at":"2026-04-18T09:26:52Z","title":"MeasHalu: Mitigation of Scientific Measurement Hallucinations for Large Language Models with Enhanced Reasoning","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-05-10T07:21:43.204609Z"},"links":{"cited_paper":"/paper/2507.01903","citing_paper":"/paper/2604.16929"},"observation_digest":"sha256:d31238de9fc70b37c12739da1677ebecb48c9737153b43fcb6c200109ac35244","observation_id":"90b72c6e-bc9a-4718-9746-b6450fbe0197","resolution":{"observed_at":"2026-05-10T07:21:55.051278Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-05-25T19:23:19.926431+00:00","source":"crossref_status_cache"},{"observed_at":"2026-05-25T19:23:19.926431+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2507.01903","last_updated":"2025-08-05T16:19:40Z","snapshot_observed_at":"2026-08-07T12:18:28.218519Z","submitted_at":"2025-07-02T17:19:20Z","title":"AI4Research: A Survey of Artificial Intelligence for Scientific Research","version":2},"cited_work":{"arxiv_id":"2507.01903","doi":"10.48550/arxiv.2507.01903","metadata_source":"arxiv_reference","pith_arxiv_id":"2507.01903","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"AI4Research","venue":"ArXiv.org","work_id":"8434d9d4-cce5-4158-b4f0-acc351e5bb4c","year":2024},"citing_paper":{"arxiv_id":"2604.19606","last_updated":"2026-04-30T03:40:02Z","snapshot_observed_at":"2026-08-03T01:53:53.879136Z","submitted_at":"2026-04-21T15:55:33Z","title":"AblateCell: A Reproduce-then-Ablate Agent for Virtual Cell Repositories","version":2},"reference_index":20,"source":"arxiv_source","source_observed_at":"2026-05-10T02:30:39.346257Z"},"links":{"cited_paper":"/paper/2507.01903","citing_paper":"/paper/2604.19606"},"observation_digest":"sha256:f539f832574501bbb26e96db83fd437298d041e1c098bafb6ac023b1429069b5","observation_id":"b5fbdd98-6bfb-4ca0-bc71-00301c3a634c","resolution":{"observed_at":"2026-05-11T13:01:04.390583Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-05-25T19:23:19.926431+00:00","source":"crossref_status_cache"},{"observed_at":"2026-05-25T19:23:19.926431+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2507.01903","last_updated":"2025-08-05T16:19:40Z","snapshot_observed_at":"2026-08-07T12:18:28.218519Z","submitted_at":"2025-07-02T17:19:20Z","title":"AI4Research: A Survey of Artificial Intelligence for Scientific Research","version":2},"cited_work":{"arxiv_id":"2507.01903","doi":"10.48550/arxiv.2507.01903","metadata_source":"arxiv_reference","pith_arxiv_id":"2507.01903","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"AI4Research","venue":"ArXiv.org","work_id":"8434d9d4-cce5-4158-b4f0-acc351e5bb4c","year":2024},"citing_paper":{"arxiv_id":"2604.20806","last_updated":"2026-04-22T17:37:40Z","snapshot_observed_at":"2026-08-02T21:32:46.195325Z","submitted_at":"2026-04-22T17:37:40Z","title":"OMIBench: Benchmarking Olympiad-Level Multi-Image Reasoning in Large Vision-Language Model","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-05-10T00:40:47.562861Z"},"links":{"cited_paper":"/paper/2507.01903","citing_paper":"/paper/2604.20806"},"observation_digest":"sha256:298d14b76965820360f777f622a983625b76b43cfc87f31c079628650db45ba7","observation_id":"c69076e0-0854-4703-879b-85dcfff49420","resolution":{"observed_at":"2026-05-11T13:46:03.395806Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-05-25T19:23:19.926431+00:00","source":"crossref_status_cache"},{"observed_at":"2026-05-25T19:23:19.926431+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2507.01903","last_updated":"2025-08-05T16:19:40Z","snapshot_observed_at":"2026-08-07T12:18:28.218519Z","submitted_at":"2025-07-02T17:19:20Z","title":"AI4Research: A Survey of Artificial Intelligence for Scientific Research","version":2},"cited_work":{"arxiv_id":"2507.01903","doi":"10.48550/arxiv.2507.01903","metadata_source":"arxiv_reference","pith_arxiv_id":"2507.01903","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"AI4Research","venue":"ArXiv.org","work_id":"8434d9d4-cce5-4158-b4f0-acc351e5bb4c","year":2024},"citing_paper":{"arxiv_id":"2604.23136","last_updated":"2026-04-25T04:35:48Z","snapshot_observed_at":"2026-07-06T23:09:23.591544Z","submitted_at":"2026-04-25T04:35:48Z","title":"How Researchers Navigate Accountability, Transparency, and Trust When Using AI Tools in Early-Stage Research: A Think-Aloud Study","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-05-08T07:21:55.049442Z"},"links":{"cited_paper":"/paper/2507.01903","citing_paper":"/paper/2604.23136"},"observation_digest":"sha256:f07f5721ab79f8232787c3133efecbe82f796b5bcef35161d3f73ce3e62f60c9","observation_id":"6beb8e1c-b3a3-425b-b2cb-47ae2f58097a","resolution":{"observed_at":"2026-05-11T21:01:12.453815Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-05-25T19:23:19.926431+00:00","source":"crossref_status_cache"},{"observed_at":"2026-05-25T19:23:19.926431+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2507.01903","last_updated":"2025-08-05T16:19:40Z","snapshot_observed_at":"2026-08-07T12:18:28.218519Z","submitted_at":"2025-07-02T17:19:20Z","title":"AI4Research: A Survey of Artificial Intelligence for Scientific Research","version":2},"cited_work":{"arxiv_id":"2507.01903","doi":"10.48550/arxiv.2507.01903","metadata_source":"arxiv_reference","pith_arxiv_id":"2507.01903","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"AI4Research","venue":"ArXiv.org","work_id":"8434d9d4-cce5-4158-b4f0-acc351e5bb4c","year":2024},"citing_paper":{"arxiv_id":"2604.23593","last_updated":"2026-04-26T08:03:32Z","snapshot_observed_at":"2026-08-01T01:43:18.294936Z","submitted_at":"2026-04-26T08:03:32Z","title":"When AI reviews science: Can we trust the referee?","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-05-08T06:19:54.727724Z"},"links":{"cited_paper":"/paper/2507.01903","citing_paper":"/paper/2604.23593"},"observation_digest":"sha256:e809bb769dadc4659e7a4da4c1725d7be104f88966d085b49040996922f1e468","observation_id":"6d6067a4-fce7-40ea-87f9-245c23ec14b9","resolution":{"observed_at":"2026-05-08T23:19:30.295275Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-05-25T19:23:19.926431+00:00","source":"crossref_status_cache"},{"observed_at":"2026-05-25T19:23:19.926431+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2507.01903","last_updated":"2025-08-05T16:19:40Z","snapshot_observed_at":"2026-08-07T12:18:28.218519Z","submitted_at":"2025-07-02T17:19:20Z","title":"AI4Research: A Survey of Artificial Intelligence for Scientific Research","version":2},"cited_work":{"arxiv_id":"2507.01903","doi":"10.48550/arxiv.2507.01903","metadata_source":"arxiv_reference","pith_arxiv_id":"2507.01903","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"AI4Research","venue":"ArXiv.org","work_id":"8434d9d4-cce5-4158-b4f0-acc351e5bb4c","year":2024},"citing_paper":{"arxiv_id":"2604.24198","last_updated":"2026-06-20T11:27:04Z","snapshot_observed_at":"2026-08-02T16:58:42.709299Z","submitted_at":"2026-04-27T09:00:30Z","title":"Rewarding the Scientific Process: Process-Level Reward Modeling for Agentic Data Analysis","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-05-08T03:47:34.897401Z"},"links":{"cited_paper":"/paper/2507.01903","citing_paper":"/paper/2604.24198"},"observation_digest":"sha256:67b768e5d3ff8b1c46b05e46519265017678faa53f7b9ac3e2fe848b8e703b86","observation_id":"c4232dc7-8c11-422b-96a9-b2c8bc99209b","resolution":{"observed_at":"2026-05-09T00:19:26.040101Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-05-25T19:23:19.926431+00:00","source":"crossref_status_cache"},{"observed_at":"2026-05-25T19:23:19.926431+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2507.01903","last_updated":"2025-08-05T16:19:40Z","snapshot_observed_at":"2026-08-07T12:18:28.218519Z","submitted_at":"2025-07-02T17:19:20Z","title":"AI4Research: A Survey of Artificial Intelligence for Scientific Research","version":2},"cited_work":{"arxiv_id":"2507.01903","doi":"10.48550/arxiv.2507.01903","metadata_source":"arxiv_reference","pith_arxiv_id":"2507.01903","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"AI4Research","venue":"ArXiv.org","work_id":"8434d9d4-cce5-4158-b4f0-acc351e5bb4c","year":2024},"citing_paper":{"arxiv_id":"2604.24198","last_updated":"2026-06-20T11:27:04Z","snapshot_observed_at":"2026-08-02T16:58:42.709299Z","submitted_at":"2026-04-27T09:00:30Z","title":"Rewarding the Scientific Process: Process-Level Reward Modeling for Agentic Data Analysis","version":2},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-07-01T09:13:20.071265Z"},"links":{"cited_paper":"/paper/2507.01903","citing_paper":"/paper/2604.24198"},"observation_digest":"sha256:4eae4853f9933eddbd0f20d036d4d4773cefacf739809fe4c2a0223bb67861f9","observation_id":"88d72abf-3384-404e-b476-96462387ce6c","resolution":{"observed_at":"2026-07-01T09:15:42.666393Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-05-25T19:23:19.926431+00:00","source":"crossref_status_cache"},{"observed_at":"2026-05-25T19:23:19.926431+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2507.01903","last_updated":"2025-08-05T16:19:40Z","snapshot_observed_at":"2026-08-07T12:18:28.218519Z","submitted_at":"2025-07-02T17:19:20Z","title":"AI4Research: A Survey of Artificial Intelligence for Scientific Research","version":2},"cited_work":{"arxiv_id":"2507.01903","doi":"10.48550/arxiv.2507.01903","metadata_source":"arxiv_reference","pith_arxiv_id":"2507.01903","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"AI4Research","venue":"ArXiv.org","work_id":"8434d9d4-cce5-4158-b4f0-acc351e5bb4c","year":2024},"citing_paper":{"arxiv_id":"2604.26645","last_updated":"2026-05-28T14:48:42Z","snapshot_observed_at":"2026-07-06T23:12:15.279847Z","submitted_at":"2026-04-29T13:11:53Z","title":"SciHorizon-DataEVA: An Agentic System for AI-Readiness Evaluation of Heterogeneous Scientific Data","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-05-07T10:54:22.054202Z"},"links":{"cited_paper":"/paper/2507.01903","citing_paper":"/paper/2604.26645"},"observation_digest":"sha256:88c99620c031d6f15b5f6455b0e96437415118dd6a20387681951e15cd775711","observation_id":"4dbe0a6a-0553-404e-81c3-96f28822fb0c","resolution":{"observed_at":"2026-05-12T09:26:26.176170Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-05-25T19:23:19.926431+00:00","source":"crossref_status_cache"},{"observed_at":"2026-05-25T19:23:19.926431+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2507.01903","last_updated":"2025-08-05T16:19:40Z","snapshot_observed_at":"2026-08-07T12:18:28.218519Z","submitted_at":"2025-07-02T17:19:20Z","title":"AI4Research: A Survey of Artificial Intelligence for Scientific Research","version":2},"cited_work":{"arxiv_id":"2507.01903","doi":"10.48550/arxiv.2507.01903","metadata_source":"arxiv_reference","pith_arxiv_id":"2507.01903","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"AI4Research","venue":"ArXiv.org","work_id":"8434d9d4-cce5-4158-b4f0-acc351e5bb4c","year":2024},"citing_paper":{"arxiv_id":"2604.27351","last_updated":"2026-04-30T03:02:27Z","snapshot_observed_at":"2026-07-06T23:12:52.141592Z","submitted_at":"2026-04-30T03:02:27Z","title":"Heterogeneous Scientific Foundation Model Collaboration","version":1},"reference_index":109,"source":"pdf_text","source_observed_at":"2026-05-07T08:50:05.980191Z"},"links":{"cited_paper":"/paper/2507.01903","citing_paper":"/paper/2604.27351"},"observation_digest":"sha256:fd4b37b1211021659972d0824d0211a7428cf7c104c1449077bea5a88d83a1ab","observation_id":"f390acf3-6418-4ae8-bd9c-17450ca6871e","resolution":{"observed_at":"2026-05-09T04:30:11.276968Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-05-25T19:23:19.926431+00:00","source":"crossref_status_cache"},{"observed_at":"2026-05-25T19:23:19.926431+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2507.01903","last_updated":"2025-08-05T16:19:40Z","snapshot_observed_at":"2026-08-07T12:18:28.218519Z","submitted_at":"2025-07-02T17:19:20Z","title":"AI4Research: A Survey of Artificial Intelligence for Scientific Research","version":2},"cited_work":{"arxiv_id":"2507.01903","doi":"10.48550/arxiv.2507.01903","metadata_source":"arxiv_reference","pith_arxiv_id":"2507.01903","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"AI4Research","venue":"ArXiv.org","work_id":"8434d9d4-cce5-4158-b4f0-acc351e5bb4c","year":2024},"citing_paper":{"arxiv_id":"2605.10246","last_updated":"2026-06-03T07:15:37Z","snapshot_observed_at":"2026-07-06T23:22:13.774652Z","submitted_at":"2026-05-11T09:19:17Z","title":"SciIntegrity-Bench: A Benchmark for Evaluating Academic Integrity in AI Scientist Systems","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-05-12T05:33:40.813795Z"},"links":{"cited_paper":"/paper/2507.01903","citing_paper":"/paper/2605.10246"},"observation_digest":"sha256:10317861688ade3f6f0d71d33b6849bace4039206ea9e6458a6a0961a25a1db4","observation_id":"ef9a9a53-f30c-4b55-a907-e1a35b1bec0c","resolution":{"observed_at":"2026-05-12T05:36:24.467870Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-05-25T19:23:19.926431+00:00","source":"crossref_status_cache"},{"observed_at":"2026-05-25T19:23:19.926431+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2507.01903","last_updated":"2025-08-05T16:19:40Z","snapshot_observed_at":"2026-08-07T12:18:28.218519Z","submitted_at":"2025-07-02T17:19:20Z","title":"AI4Research: A Survey of Artificial Intelligence for Scientific Research","version":2},"cited_work":{"arxiv_id":"2507.01903","doi":"10.48550/arxiv.2507.01903","metadata_source":"arxiv_reference","pith_arxiv_id":"2507.01903","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"AI4Research","venue":"ArXiv.org","work_id":"8434d9d4-cce5-4158-b4f0-acc351e5bb4c","year":2024},"citing_paper":{"arxiv_id":"2605.10246","last_updated":"2026-06-03T07:15:37Z","snapshot_observed_at":"2026-07-06T23:22:13.774652Z","submitted_at":"2026-05-11T09:19:17Z","title":"SciIntegrity-Bench: A Benchmark for Evaluating Academic Integrity in AI Scientist Systems","version":2},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-06-30T22:48:43.262187Z"},"links":{"cited_paper":"/paper/2507.01903","citing_paper":"/paper/2605.10246"},"observation_digest":"sha256:3264762f35783d0ebc8c8ebd5694509c91412a9e2cf01c5d62c72b23a986add4","observation_id":"af2091c1-a52a-4635-8cdb-14ecb40e8789","resolution":{"observed_at":"2026-07-01T13:45:45.896486Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-05-25T19:23:19.926431+00:00","source":"crossref_status_cache"},{"observed_at":"2026-05-25T19:23:19.926431+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2507.01903","last_updated":"2025-08-05T16:19:40Z","snapshot_observed_at":"2026-08-07T12:18:28.218519Z","submitted_at":"2025-07-02T17:19:20Z","title":"AI4Research: A Survey of Artificial Intelligence for Scientific Research","version":2},"cited_work":{"arxiv_id":"2507.01903","doi":"10.48550/arxiv.2507.01903","metadata_source":"arxiv_reference","pith_arxiv_id":"2507.01903","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"AI4Research","venue":"ArXiv.org","work_id":"8434d9d4-cce5-4158-b4f0-acc351e5bb4c","year":2024},"citing_paper":{"arxiv_id":"2605.16508","last_updated":"2026-05-15T18:05:21Z","snapshot_observed_at":"2026-08-03T01:50:34.102829Z","submitted_at":"2026-05-15T18:05:21Z","title":"The Scaling Laws of Skills in LLM Agent Systems","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-05-20T18:10:08.737710Z"},"links":{"cited_paper":"/paper/2507.01903","citing_paper":"/paper/2605.16508"},"observation_digest":"sha256:df8ebb9df0c3fbc98fc74f4f275d346197b26f3f85fcf6ad8471ea5c2e641a12","observation_id":"3f4468cb-6236-49e1-8623-da83a4b65232","resolution":{"observed_at":"2026-05-20T18:13:37.629993Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-05-25T19:23:19.926431+00:00","source":"crossref_status_cache"},{"observed_at":"2026-05-25T19:23:19.926431+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2507.01903","last_updated":"2025-08-05T16:19:40Z","snapshot_observed_at":"2026-08-07T12:18:28.218519Z","submitted_at":"2025-07-02T17:19:20Z","title":"AI4Research: A Survey of Artificial Intelligence for Scientific Research","version":2},"cited_work":{"arxiv_id":"2507.01903","doi":"10.48550/arxiv.2507.01903","metadata_source":"arxiv_reference","pith_arxiv_id":"2507.01903","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"AI4Research","venue":"ArXiv.org","work_id":"8434d9d4-cce5-4158-b4f0-acc351e5bb4c","year":2024},"citing_paper":{"arxiv_id":"2605.18661","last_updated":"2026-07-20T17:24:03Z","snapshot_observed_at":"2026-08-02T13:43:29.187658Z","submitted_at":"2026-05-18T17:08:26Z","title":"AI for Auto-Research: Roadmap & User Guide","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-05-20T10:30:50.256635Z"},"links":{"cited_paper":"/paper/2507.01903","citing_paper":"/paper/2605.18661"},"observation_digest":"sha256:4b79fd808eec07b8bb4fc509e08a66debd85a2c75a3a3ea7ef43a1cf6fdbc613","observation_id":"1dddd341-64c2-40da-a720-9a5eb11a6f1a","resolution":{"observed_at":"2026-05-20T10:33:12.786740Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-05-25T19:23:19.926431+00:00","source":"crossref_status_cache"},{"observed_at":"2026-05-25T19:23:19.926431+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2507.01903","last_updated":"2025-08-05T16:19:40Z","snapshot_observed_at":"2026-08-07T12:18:28.218519Z","submitted_at":"2025-07-02T17:19:20Z","title":"AI4Research: A Survey of Artificial Intelligence for Scientific Research","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2507.01903","snapshot_observed_at":"2026-08-02T13:43:32.799207Z","title":null,"venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2605.18661","last_updated":"2026-07-20T17:24:03Z","snapshot_observed_at":"2026-08-02T13:43:29.187658Z","submitted_at":"2026-05-18T17:08:26Z","title":"AI for Auto-Research: Roadmap & User Guide","version":2},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-02T13:43:32.799207Z"},"links":{"cited_paper":"/paper/2507.01903","citing_paper":"/paper/2605.18661"},"observation_digest":"sha256:af38a5a2624a1d0be9ce3d02befa66a5add833bed3ec2b2234ea5550a7588b7b","observation_id":"3f089458-9e96-460d-964e-c6ba380d9a35","resolution":{"observed_at":"2026-08-02T13:43:32.799207Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2507.01903","last_updated":"2025-08-05T16:19:40Z","snapshot_observed_at":"2026-08-07T12:18:28.218519Z","submitted_at":"2025-07-02T17:19:20Z","title":"AI4Research: A Survey of Artificial Intelligence for Scientific Research","version":2},"cited_work":{"arxiv_id":"2507.01903","doi":"10.48550/arxiv.2507.01903","metadata_source":"arxiv_reference","pith_arxiv_id":"2507.01903","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"AI4Research","venue":"ArXiv.org","work_id":"8434d9d4-cce5-4158-b4f0-acc351e5bb4c","year":2024},"citing_paper":{"arxiv_id":"2605.22878","last_updated":"2026-05-20T16:03:29Z","snapshot_observed_at":"2026-07-06T23:33:09.561760Z","submitted_at":"2026-05-20T16:03:29Z","title":"SciAtlas: A Large-Scale Knowledge Graph for Automated Scientific Research","version":1},"reference_index":6,"source":"arxiv_source","source_observed_at":"2026-05-25T05:45:54.275921Z"},"links":{"cited_paper":"/paper/2507.01903","citing_paper":"/paper/2605.22878"},"observation_digest":"sha256:472095c88be6e99fb3ac7420144a809fbe4fc1059ecf61fab40d8cf068c97458","observation_id":"ed984b9d-338a-482d-9a0e-99f28b40858f","resolution":{"observed_at":"2026-05-25T05:46:39.353393Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-05-25T19:23:19.926431+00:00","source":"crossref_status_cache"},{"observed_at":"2026-05-25T19:23:19.926431+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2507.01903","last_updated":"2025-08-05T16:19:40Z","snapshot_observed_at":"2026-08-07T12:18:28.218519Z","submitted_at":"2025-07-02T17:19:20Z","title":"AI4Research: A Survey of Artificial Intelligence for Scientific Research","version":2},"cited_work":{"arxiv_id":"2507.01903","doi":"10.48550/arxiv.2507.01903","metadata_source":"arxiv_reference","pith_arxiv_id":"2507.01903","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"AI4Research","venue":"ArXiv.org","work_id":"8434d9d4-cce5-4158-b4f0-acc351e5bb4c","year":2024},"citing_paper":{"arxiv_id":"2605.23204","last_updated":"2026-05-22T03:40:30Z","snapshot_observed_at":"2026-07-06T23:33:29.550551Z","submitted_at":"2026-05-22T03:40:30Z","title":"AutoResearch AI: Towards AI-Powered Research Automation for Scientific Discovery","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-05-25T04:46:43.679185Z"},"links":{"cited_paper":"/paper/2507.01903","citing_paper":"/paper/2605.23204"},"observation_digest":"sha256:43f44e02cfa913867d08e01448f2c23e3abc0bb7f408a467e61892eba7b128be","observation_id":"acaf9142-355b-46a0-b943-a79e0cc8b24b","resolution":{"observed_at":"2026-05-25T04:50:21.616419Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-05-25T19:23:19.926431+00:00","source":"crossref_status_cache"},{"observed_at":"2026-05-25T19:23:19.926431+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2507.01903","last_updated":"2025-08-05T16:19:40Z","snapshot_observed_at":"2026-08-07T12:18:28.218519Z","submitted_at":"2025-07-02T17:19:20Z","title":"AI4Research: A Survey of Artificial Intelligence for Scientific Research","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2507.01903","snapshot_observed_at":"2026-07-12T16:14:01.560420Z","title":"Ai4research: A survey of artificial intelligence for scientific research.arXiv preprint arXiv:2507.01903, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2605.24042","last_updated":"2026-07-06T17:37:14Z","snapshot_observed_at":"2026-08-07T12:19:08.745607Z","submitted_at":"2026-05-21T20:12:09Z","title":"Hidden-State Privacy Has an Empty Middle","version":3},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-07-12T16:14:01.560420Z"},"links":{"cited_paper":"/paper/2507.01903","citing_paper":"/paper/2605.24042"},"observation_digest":"sha256:4c42dccd4115cabbef6e880d92392eeb5385887d00a681af0f10b1ca17b8336c","observation_id":"96d11e0f-0564-4018-b0f6-ecf4484e3914","resolution":{"observed_at":"2026-07-12T16:14:01.560420Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2507.01903","last_updated":"2025-08-05T16:19:40Z","snapshot_observed_at":"2026-08-07T12:18:28.218519Z","submitted_at":"2025-07-02T17:19:20Z","title":"AI4Research: A Survey of Artificial Intelligence for Scientific Research","version":2},"cited_work":{"arxiv_id":"2507.01903","doi":"10.48550/arxiv.2507.01903","metadata_source":"arxiv_reference","pith_arxiv_id":"2507.01903","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"AI4Research","venue":"ArXiv.org","work_id":"8434d9d4-cce5-4158-b4f0-acc351e5bb4c","year":2024},"citing_paper":{"arxiv_id":"2605.24043","last_updated":"2026-05-21T20:30:56Z","snapshot_observed_at":"2026-07-06T23:34:08.786038Z","submitted_at":"2026-05-21T20:30:56Z","title":"LLM-AutoSciLab: Closed-Loop Scientific Discovery via Active Experimentation with LLMs","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-06-30T16:55:32.815360Z"},"links":{"cited_paper":"/paper/2507.01903","citing_paper":"/paper/2605.24043"},"observation_digest":"sha256:6caafe64bf8dd786831286e40ef53b4e10f64535fd19a3a0856feb3f8b352dae","observation_id":"f4cd2625-85e1-44ef-ba22-7c8108285923","resolution":{"observed_at":"2026-06-30T17:04:57.781581Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-05-25T19:23:19.926431+00:00","source":"crossref_status_cache"},{"observed_at":"2026-05-25T19:23:19.926431+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2507.01903","last_updated":"2025-08-05T16:19:40Z","snapshot_observed_at":"2026-08-07T12:18:28.218519Z","submitted_at":"2025-07-02T17:19:20Z","title":"AI4Research: A Survey of Artificial Intelligence for Scientific Research","version":2},"cited_work":{"arxiv_id":"2507.01903","doi":"10.48550/arxiv.2507.01903","metadata_source":"arxiv_reference","pith_arxiv_id":"2507.01903","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"AI4Research","venue":"ArXiv.org","work_id":"8434d9d4-cce5-4158-b4f0-acc351e5bb4c","year":2024},"citing_paper":{"arxiv_id":"2606.01013","last_updated":"2026-06-02T06:07:26Z","snapshot_observed_at":"2026-08-05T16:58:56.629771Z","submitted_at":"2026-05-31T05:05:26Z","title":"Can AI Review Improve Paper Drafting? An Empirical Study on 20 Computer Architecture Submissions","version":2},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-06-28T17:27:59.500885Z"},"links":{"cited_paper":"/paper/2507.01903","citing_paper":"/paper/2606.01013"},"observation_digest":"sha256:e884d24000553e4f5fe1b46cc2e71c95d4ad0746568231c21eeb40c585acb08a","observation_id":"8d44ec6a-090e-4ae7-996f-4f7bbdedfc04","resolution":{"observed_at":"2026-07-01T21:06:14.503496Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-05-25T19:23:19.926431+00:00","source":"crossref_status_cache"},{"observed_at":"2026-05-25T19:23:19.926431+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2507.01903","last_updated":"2025-08-05T16:19:40Z","snapshot_observed_at":"2026-08-07T12:18:28.218519Z","submitted_at":"2025-07-02T17:19:20Z","title":"AI4Research: A Survey of Artificial Intelligence for Scientific Research","version":2},"cited_work":{"arxiv_id":"2507.01903","doi":"10.48550/arxiv.2507.01903","metadata_source":"arxiv_reference","pith_arxiv_id":"2507.01903","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"AI4Research","venue":"ArXiv.org","work_id":"8434d9d4-cce5-4158-b4f0-acc351e5bb4c","year":2024},"citing_paper":{"arxiv_id":"2606.22188","last_updated":"2026-06-20T18:41:28Z","snapshot_observed_at":"2026-08-06T09:15:45.888157Z","submitted_at":"2026-06-20T18:41:28Z","title":"Bayesian Adaptation Gym: A Benchmark for the Bayesian Low-Rank Adaptation of Multi-Modal Language Models","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-06-26T12:07:15.289430Z"},"links":{"cited_paper":"/paper/2507.01903","citing_paper":"/paper/2606.22188"},"observation_digest":"sha256:ade3a6c2581e44be4f01fbecc2b367c5c95c231bb394d14f0fe2ad9949b3a360","observation_id":"4a17df71-8e15-4912-bba2-f483f3a27b26","resolution":{"observed_at":"2026-07-04T08:09:41.596937Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-05-25T19:23:19.926431+00:00","source":"crossref_status_cache"},{"observed_at":"2026-05-25T19:23:19.926431+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2507.01903","last_updated":"2025-08-05T16:19:40Z","snapshot_observed_at":"2026-08-07T12:18:28.218519Z","submitted_at":"2025-07-02T17:19:20Z","title":"AI4Research: A Survey of Artificial Intelligence for Scientific Research","version":2},"cited_work":{"arxiv_id":"2507.01903","doi":"10.48550/arxiv.2507.01903","metadata_source":"arxiv_reference","pith_arxiv_id":"2507.01903","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"AI4Research","venue":"ArXiv.org","work_id":"8434d9d4-cce5-4158-b4f0-acc351e5bb4c","year":2024},"citing_paper":{"arxiv_id":"2606.23233","last_updated":"2026-06-22T12:20:11Z","snapshot_observed_at":"2026-08-01T14:51:19.286742Z","submitted_at":"2026-06-22T12:20:11Z","title":"Judgment-Grounded Expansion for Peer Review Generation","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-06-26T08:28:40.913343Z"},"links":{"cited_paper":"/paper/2507.01903","citing_paper":"/paper/2606.23233"},"observation_digest":"sha256:85b0d3049c5df72369e83ed192ac034d89d70865cd511db98d4b82f592a5c9bb","observation_id":"4fbd5770-11ca-4609-b5f3-48389ed8041c","resolution":{"observed_at":"2026-07-04T10:49:46.277274Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-05-25T19:23:19.926431+00:00","source":"crossref_status_cache"},{"observed_at":"2026-05-25T19:23:19.926431+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2507.01903","last_updated":"2025-08-05T16:19:40Z","snapshot_observed_at":"2026-08-07T12:18:28.218519Z","submitted_at":"2025-07-02T17:19:20Z","title":"AI4Research: A Survey of Artificial Intelligence for Scientific Research","version":2},"cited_work":{"arxiv_id":"2507.01903","doi":"10.48550/arxiv.2507.01903","metadata_source":"arxiv_reference","pith_arxiv_id":"2507.01903","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"AI4Research","venue":"ArXiv.org","work_id":"8434d9d4-cce5-4158-b4f0-acc351e5bb4c","year":2024},"citing_paper":{"arxiv_id":"2606.29981","last_updated":"2026-06-29T08:56:37Z","snapshot_observed_at":"2026-08-04T22:43:17.516748Z","submitted_at":"2026-06-29T08:56:37Z","title":"Hephaestus: Toward a Cybersecurity AI Scientist","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-06-30T05:42:32.460183Z"},"links":{"cited_paper":"/paper/2507.01903","citing_paper":"/paper/2606.29981"},"observation_digest":"sha256:61bf6afea624f60849e43b631fa56d42ef1bb66961d5d886e3dce961b7ec4c18","observation_id":"d052fa48-fc36-4d76-a07c-48d7d68e4b94","resolution":{"observed_at":"2026-06-30T13:54:44.429514Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-05-25T19:23:19.926431+00:00","source":"crossref_status_cache"},{"observed_at":"2026-05-25T19:23:19.926431+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2507.01903","last_updated":"2025-08-05T16:19:40Z","snapshot_observed_at":"2026-08-07T12:18:28.218519Z","submitted_at":"2025-07-02T17:19:20Z","title":"AI4Research: A Survey of Artificial Intelligence for Scientific Research","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2507.01903","snapshot_observed_at":"2026-07-13T00:55:17.107245Z","title":null,"venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.09025","last_updated":"2026-07-10T01:09:38Z","snapshot_observed_at":"2026-08-07T07:51:36.554305Z","submitted_at":"2026-07-10T01:09:38Z","title":"Evolutionary Intelligence for Scientific Discovery: From Evolutionary Computation to Cumulative Discovery Systems","version":1},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-07-13T00:55:17.107245Z"},"links":{"cited_paper":"/paper/2507.01903","citing_paper":"/paper/2607.09025"},"observation_digest":"sha256:3badffb294cbdedc60bcadc72de0f85a78615c7062092d7d6e9919af79e4a027","observation_id":"7e4ce110-9160-411d-80f0-b12fef958dc4","resolution":{"observed_at":"2026-07-13T00:55:17.107245Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2507.01903","last_updated":"2025-08-05T16:19:40Z","snapshot_observed_at":"2026-08-07T12:18:28.218519Z","submitted_at":"2025-07-02T17:19:20Z","title":"AI4Research: A Survey of Artificial Intelligence for Scientific Research","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2507.01903","snapshot_observed_at":"2026-08-01T01:15:07.213988Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.25886","last_updated":"2026-07-28T15:46:41Z","snapshot_observed_at":"2026-08-07T09:45:34.637759Z","submitted_at":"2026-07-28T15:46:41Z","title":"RSIBench-Data: Benchmarking Data-Centric Research for Recursive Self-Improvement","version":1},"reference_index":17,"source":"arxiv_source","source_observed_at":"2026-08-01T01:15:07.213988Z"},"links":{"cited_paper":"/paper/2507.01903","citing_paper":"/paper/2607.25886"},"observation_digest":"sha256:a3af3ec09e5ea8a911bed5be008477e6c85591870c4a158ef3b22aeb754e8382","observation_id":"3f4f6491-6faa-4656-a876-a93620a1540d","resolution":{"observed_at":"2026-08-01T01:15:07.213988Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2507.01903/citation-record","integrity":"/paper/2507.01903/integrity","json":"/paper/2507.01903/citation-record.json","paper":"/paper/2507.01903"},"outbound":[{"citation":{"cited_paper":{"arxiv_id":"2412.08905","last_updated":"2024-12-12T03:37:41Z","snapshot_observed_at":"2026-08-05T04:04:21.846023Z","submitted_at":"2024-12-12T03:37:41Z","title":"Phi-4 Technical Report","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2412.08905","snapshot_observed_at":"2026-08-06T20:45:08.109329Z","title":"Phi-4 technical report.arXiv preprint arXiv:2412.08905, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.01903","last_updated":"2025-08-05T16:19:40Z","snapshot_observed_at":"2026-08-07T12:18:28.218519Z","submitted_at":"2025-07-02T17:19:20Z","title":"AI4Research: A Survey of Artificial Intelligence for Scientific Research","version":2},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-06T20:45:08.109329Z"},"links":{"cited_paper":"/paper/2412.08905","citing_paper":"/paper/2507.01903"},"observation_digest":"sha256:bdff7ff4bd274bd744b3f5ff0af48db81e192675e1c4811ff44c2e976f8bf5db","observation_id":"0f9b9160-97ce-4790-a92b-6eff9409b983","resolution":{"observed_at":"2026-08-06T20:45:08.109329Z","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":"2026-08-06T20:45:08.263027Z","title":"Accurate structure prediction of biomolecular interactions with alphafold 3.Nature, 630(8016):493–500, May 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.01903","last_updated":"2025-08-05T16:19:40Z","snapshot_observed_at":"2026-08-07T12:18:28.218519Z","submitted_at":"2025-07-02T17:19:20Z","title":"AI4Research: A Survey of Artificial Intelligence for Scientific Research","version":2},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-06T20:45:08.263027Z"},"links":{"citing_paper":"/paper/2507.01903"},"observation_digest":"sha256:bc28fb3a301d236047b1e2ebd668021ae16ea9a2db17e7f843710663af60300e","observation_id":"edabbd39-4108-4476-b66b-2582d3f7444a","resolution":{"observed_at":"2026-08-06T20:45:08.263027Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2303.08774","last_updated":"2024-03-04T06:01:33Z","snapshot_observed_at":"2026-08-07T07:30:12.213965Z","submitted_at":"2023-03-15T17:15:04Z","title":"GPT-4 Technical Report","version":6},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2303.08774","snapshot_observed_at":"2026-08-06T20:45:08.388205Z","title":"Gpt-4 technical report","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2507.01903","last_updated":"2025-08-05T16:19:40Z","snapshot_observed_at":"2026-08-07T12:18:28.218519Z","submitted_at":"2025-07-02T17:19:20Z","title":"AI4Research: A Survey of Artificial Intelligence for Scientific Research","version":2},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-06T20:45:08.388205Z"},"links":{"cited_paper":"/paper/2303.08774","citing_paper":"/paper/2507.01903"},"observation_digest":"sha256:a7910ba29c625ee1e1d940a2c38221e5e95f2dc360bc2cd439767e76bfae5d38","observation_id":"60e22d64-00d7-400a-9f09-c386e411f390","resolution":{"observed_at":"2026-08-06T20:45:08.388205Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2505.16349","last_updated":"2025-05-22T08:00:59Z","snapshot_observed_at":"2026-08-07T15:00:42.966066Z","submitted_at":"2025-05-22T08:00:59Z","title":"Ask, Retrieve, Summarize: A Modular Pipeline for Scientific Literature Summarization","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2505.16349","snapshot_observed_at":"2026-08-06T20:45:08.455197Z","title":"Ask, retrieve, summarize: A modular pipeline for scientific literature summarization.arXiv preprint arXiv:2505.16349, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2507.01903","last_updated":"2025-08-05T16:19:40Z","snapshot_observed_at":"2026-08-07T12:18:28.218519Z","submitted_at":"2025-07-02T17:19:20Z","title":"AI4Research: A Survey of Artificial Intelligence for Scientific Research","version":2},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-06T20:45:08.455197Z"},"links":{"cited_paper":"/paper/2505.16349","citing_paper":"/paper/2507.01903"},"observation_digest":"sha256:796772ba9a9a7ee323a3c25115f3d5f346a4e5d9cfe479db4990ef8a67c7bf13","observation_id":"fa139a4d-031d-4127-b698-4a890a0c9e43","resolution":{"observed_at":"2026-08-06T20:45:08.455197Z","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":"2026-08-06T20:45:08.523425Z","title":"Efficient bayesian learningcurveextrapolationusingprior-datafittednetworks","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2507.01903","last_updated":"2025-08-05T16:19:40Z","snapshot_observed_at":"2026-08-07T12:18:28.218519Z","submitted_at":"2025-07-02T17:19:20Z","title":"AI4Research: A Survey of Artificial Intelligence for Scientific Research","version":2},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-06T20:45:08.523425Z"},"links":{"citing_paper":"/paper/2507.01903"},"observation_digest":"sha256:30247e6fda6dc2b1a77c178bfa9c77b64132cb5c16b3e57a43f3c26e0c31fe73","observation_id":"817fb7d8-716b-46b6-b884-1811c7d95bdb","resolution":{"observed_at":"2026-08-06T20:45:08.523425Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.15828","last_updated":"2024-10-21T09:46:37Z","snapshot_observed_at":"2026-08-07T18:05:41.942135Z","submitted_at":"2024-10-21T09:46:37Z","title":"LLM4GRN: Discovering Causal Gene Regulatory Networks with LLMs -- Evaluation through Synthetic Data Generation","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.15828","snapshot_observed_at":"2026-08-06T20:45:08.575958Z","title":"Llm4grn: Discovering causal gene regulatory networks with llms–evaluation through synthetic data generation.arXiv preprint arXiv:2410.15828, 2024","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2507.01903","last_updated":"2025-08-05T16:19:40Z","snapshot_observed_at":"2026-08-07T12:18:28.218519Z","submitted_at":"2025-07-02T17:19:20Z","title":"AI4Research: A Survey of Artificial Intelligence for Scientific Research","version":2},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-06T20:45:08.575958Z"},"links":{"cited_paper":"/paper/2410.15828","citing_paper":"/paper/2507.01903"},"observation_digest":"sha256:b48ece0c02a8c3d492a98570afa0f34822bd2f094df2567a9c1b04054eaf0a02","observation_id":"4807a835-a9d7-4da2-b879-7000fea00fb4","resolution":{"observed_at":"2026-08-06T20:45:08.575958Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2402.01788","last_updated":"2025-03-21T14:49:10Z","snapshot_observed_at":"2026-08-04T15:15:21.414953Z","submitted_at":"2024-02-02T02:41:28Z","title":"LitLLM: A Toolkit for Scientific Literature Review","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.01788","snapshot_observed_at":"2026-08-06T20:45:08.640354Z","title":"Litllm: A toolkit for scientific literature review.arXiv preprint arXiv:2402.01788, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.01903","last_updated":"2025-08-05T16:19:40Z","snapshot_observed_at":"2026-08-07T12:18:28.218519Z","submitted_at":"2025-07-02T17:19:20Z","title":"AI4Research: A Survey of Artificial Intelligence for Scientific Research","version":2},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-06T20:45:08.640354Z"},"links":{"cited_paper":"/paper/2402.01788","citing_paper":"/paper/2507.01903"},"observation_digest":"sha256:6e968687e257f63bf8ebd02403983438ae28c4c581c7930c353822067f48dd50","observation_id":"981e86aa-6ce1-4f1d-965b-aee7fa959f87","resolution":{"observed_at":"2026-08-06T20:45:08.640354Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2412.15249","last_updated":"2025-03-21T14:56:58Z","snapshot_observed_at":"2026-07-06T20:10:24.217625Z","submitted_at":"2024-12-15T01:12:26Z","title":"LitLLMs, LLMs for Literature Review: Are we there yet?","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2412.15249","snapshot_observed_at":"2026-08-06T20:45:08.684361Z","title":"Llms for literature review: Are we there yet?arXiv preprint arXiv:2412.15249, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.01903","last_updated":"2025-08-05T16:19:40Z","snapshot_observed_at":"2026-08-07T12:18:28.218519Z","submitted_at":"2025-07-02T17:19:20Z","title":"AI4Research: A Survey of Artificial Intelligence for Scientific Research","version":2},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-06T20:45:08.684361Z"},"links":{"cited_paper":"/paper/2412.15249","citing_paper":"/paper/2507.01903"},"observation_digest":"sha256:b79e33479bc8858c5603411bf4b3df1060b0a013f00fa909292dc91b3d2b41eb","observation_id":"7f38c6ee-7c88-41ee-8569-b0427bf4aa9e","resolution":{"observed_at":"2026-08-06T20:45:08.684361Z","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":"2026-08-06T20:45:08.759039Z","title":"Laradji, Krishnamurthy Dj Dvijotham, Jason Stanley, Laurent Charlin, and Christopher Pal","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2507.01903","last_updated":"2025-08-05T16:19:40Z","snapshot_observed_at":"2026-08-07T12:18:28.218519Z","submitted_at":"2025-07-02T17:19:20Z","title":"AI4Research: A Survey of Artificial Intelligence for Scientific Research","version":2},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-06T20:45:08.759039Z"},"links":{"citing_paper":"/paper/2507.01903"},"observation_digest":"sha256:7965ca3b2ccbe6fb3c9e0ceda7d3372a71ddc56a741ced3443282f4a79d9bc77","observation_id":"834a9668-8009-4f41-832b-e6cfc5ffb8ab","resolution":{"observed_at":"2026-08-06T20:45:08.759039Z","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":"2026-08-06T20:45:08.851631Z","title":"Artificial intelligence and scientific discovery: A model of prioritized search.Research Policy, 53(5):104989, Jun 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.01903","last_updated":"2025-08-05T16:19:40Z","snapshot_observed_at":"2026-08-07T12:18:28.218519Z","submitted_at":"2025-07-02T17:19:20Z","title":"AI4Research: A Survey of Artificial Intelligence for Scientific Research","version":2},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-06T20:45:08.851631Z"},"links":{"citing_paper":"/paper/2507.01903"},"observation_digest":"sha256:291de15ed6805df5f53e3cd7cfaf148c3a732e06a40e58925f533cd8c6d3e7bf","observation_id":"1ca698a1-17ed-4c26-9395-6a397f4d02c0","resolution":{"observed_at":"2026-08-06T20:45:08.851631Z","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":"2026-08-06T20:45:08.910287Z","title":"Ml-gap: machine learning-enhanced genomic analysis pipeline using autoencoders and data augmentation.Frontiers in Genetics, 15:1442759, Sep 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.01903","last_updated":"2025-08-05T16:19:40Z","snapshot_observed_at":"2026-08-07T12:18:28.218519Z","submitted_at":"2025-07-02T17:19:20Z","title":"AI4Research: A Survey of Artificial Intelligence for Scientific Research","version":2},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-06T20:45:08.910287Z"},"links":{"citing_paper":"/paper/2507.01903"},"observation_digest":"sha256:7692089e2b82e21a7c5fc64c30efe66298497cad4bc5967001b0cb416791c76e","observation_id":"b0ebcc17-f66c-4b37-ae32-9c643a22a55f","resolution":{"observed_at":"2026-08-06T20:45:08.910287Z","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":"2026-08-06T20:45:09.014289Z","title":"Zochi technical report, Mar 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2507.01903","last_updated":"2025-08-05T16:19:40Z","snapshot_observed_at":"2026-08-07T12:18:28.218519Z","submitted_at":"2025-07-02T17:19:20Z","title":"AI4Research: A Survey of Artificial Intelligence for Scientific Research","version":2},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-06T20:45:09.014289Z"},"links":{"citing_paper":"/paper/2507.01903"},"observation_digest":"sha256:911ab75105b982ee3a0fc36d9de532ebf9e6bbc6b932c2b6fe90d889b096d8c6","observation_id":"166be019-76ec-4d02-8b69-0f1a4a8c5675","resolution":{"observed_at":"2026-08-06T20:45:09.014289Z","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":"2026-08-06T20:45:09.094051Z","title":"Autonomousmachinelearning-basedpeerreviewer selection system","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2507.01903","last_updated":"2025-08-05T16:19:40Z","snapshot_observed_at":"2026-08-07T12:18:28.218519Z","submitted_at":"2025-07-02T17:19:20Z","title":"AI4Research: A Survey of Artificial Intelligence for Scientific Research","version":2},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-06T20:45:09.094051Z"},"links":{"citing_paper":"/paper/2507.01903"},"observation_digest":"sha256:095f1119c4239ed7863fddd028b914b432e8fd35705f8f865312cf5ce3ddb605","observation_id":"8eaed2c7-1e48-4fe4-8efe-b7c5af9d8ccf","resolution":{"observed_at":"2026-08-06T20:45:09.094051Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2504.02767","last_updated":"2025-04-03T17:04:56Z","snapshot_observed_at":"2026-08-07T16:10:53.779327Z","submitted_at":"2025-04-03T17:04:56Z","title":"How Deep Do Large Language Models Internalize Scientific Literature and Citation Practices?","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2504.02767","snapshot_observed_at":"2026-08-06T20:45:09.171559Z","title":"How deep do large language models internalize scientific literature and citation practices? arXiv preprint arXiv:2504.02767, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2507.01903","last_updated":"2025-08-05T16:19:40Z","snapshot_observed_at":"2026-08-07T12:18:28.218519Z","submitted_at":"2025-07-02T17:19:20Z","title":"AI4Research: A Survey of Artificial Intelligence for Scientific Research","version":2},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-06T20:45:09.171559Z"},"links":{"cited_paper":"/paper/2504.02767","citing_paper":"/paper/2507.01903"},"observation_digest":"sha256:21ee427f0842bd4d5c5ec14c99accbfa5eae5d1ad94294accdaa456bb32f6c9d","observation_id":"c41ccc49-ff53-44ea-8216-7bd3a6a0a76d","resolution":{"observed_at":"2026-08-06T20:45:09.171559Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2504.05496","last_updated":"2025-04-07T20:44:33Z","snapshot_observed_at":"2026-08-07T16:07:47.414759Z","submitted_at":"2025-04-07T20:44:33Z","title":"A Survey on Hypothesis Generation for Scientific Discovery in the Era of Large Language Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2504.05496","snapshot_observed_at":"2026-08-06T20:45:09.273656Z","title":"A survey on hypothesis generation for scientific discovery in the era of large language models.arXiv preprint arXiv:2504.05496, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2507.01903","last_updated":"2025-08-05T16:19:40Z","snapshot_observed_at":"2026-08-07T12:18:28.218519Z","submitted_at":"2025-07-02T17:19:20Z","title":"AI4Research: A Survey of Artificial Intelligence for Scientific Research","version":2},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-06T20:45:09.273656Z"},"links":{"cited_paper":"/paper/2504.05496","citing_paper":"/paper/2507.01903"},"observation_digest":"sha256:2acd383f8da826417f1380786967f3325130c4f051edc77ec7449cdc613115c3","observation_id":"5bb67d52-c72b-4b35-8992-a5035246d9ca","resolution":{"observed_at":"2026-08-06T20:45:09.273656Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2305.07796","last_updated":"2023-05-12T23:09:26Z","snapshot_observed_at":"2026-07-06T15:26:42.770863Z","submitted_at":"2023-05-12T23:09:26Z","title":"aedFaCT: Scientific Fact-Checking Made Easier via Semi-Automatic Discovery of Relevant Expert Opinions","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2305.07796","snapshot_observed_at":"2026-08-06T20:45:09.358853Z","title":"aedfact: Scientific fact-checking made easier via semi-automatic discovery of relevant expert opinions.arXiv preprint arXiv:2305.07796, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2507.01903","last_updated":"2025-08-05T16:19:40Z","snapshot_observed_at":"2026-08-07T12:18:28.218519Z","submitted_at":"2025-07-02T17:19:20Z","title":"AI4Research: A Survey of Artificial Intelligence for Scientific Research","version":2},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-06T20:45:09.358853Z"},"links":{"cited_paper":"/paper/2305.07796","citing_paper":"/paper/2507.01903"},"observation_digest":"sha256:ed3e2c68f7e23e3bb0cfa3c62b96899ee3e5a1d82223f0f47a6607afd34122a5","observation_id":"22377e3a-ee11-47ac-a0e3-0da13c7a4b90","resolution":{"observed_at":"2026-08-06T20:45:09.358853Z","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":"2026-08-06T20:45:09.421325Z","title":"Zero-shot scientific claim verification using llms and citation text","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.01903","last_updated":"2025-08-05T16:19:40Z","snapshot_observed_at":"2026-08-07T12:18:28.218519Z","submitted_at":"2025-07-02T17:19:20Z","title":"AI4Research: A Survey of Artificial Intelligence for Scientific Research","version":2},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-06T20:45:09.421325Z"},"links":{"citing_paper":"/paper/2507.01903"},"observation_digest":"sha256:d0621b52e04033f5588081a188b38fc819f5811e0a52f605566532c37872c3ad","observation_id":"a9019ba1-54b6-486b-887f-072714c92f54","resolution":{"observed_at":"2026-08-06T20:45:09.421325Z","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":"2026-08-06T20:45:09.519967Z","title":"Policy advice and best practices on bias and fairness in ai.Ethics and Information Technology, 26(2):31, Apr 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.01903","last_updated":"2025-08-05T16:19:40Z","snapshot_observed_at":"2026-08-07T12:18:28.218519Z","submitted_at":"2025-07-02T17:19:20Z","title":"AI4Research: A Survey of Artificial Intelligence for Scientific Research","version":2},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-06T20:45:09.519967Z"},"links":{"citing_paper":"/paper/2507.01903"},"observation_digest":"sha256:9939b7ada726df70f89ec36e9552d82ff6600a3f95a3f0d76e96c394c5b135f3","observation_id":"1da51b0e-f3b4-48f7-9dde-cd22b5946c85","resolution":{"observed_at":"2026-08-06T20:45:09.519967Z","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":"2026-08-06T20:45:09.584172Z","title":"Languages are still a major barrier to global science.PLoS biology, 14(12):e2000933, Dec 2016","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2507.01903","last_updated":"2025-08-05T16:19:40Z","snapshot_observed_at":"2026-08-07T12:18:28.218519Z","submitted_at":"2025-07-02T17:19:20Z","title":"AI4Research: A Survey of Artificial Intelligence for Scientific Research","version":2},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-06T20:45:09.584172Z"},"links":{"citing_paper":"/paper/2507.01903"},"observation_digest":"sha256:98185d7ac843a7df9b54edcbc4c6cdc65ae04f553d33b3ea630c4bd0d69433e3","observation_id":"0906d54d-aecd-499c-9cfe-4f3216358cf9","resolution":{"observed_at":"2026-08-06T20:45:09.584172Z","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":"2026-08-06T20:45:09.686769Z","title":"Ten tips for overcoming language barriers in science.Nature Human Behaviour, 5(9):1119–1122, Jul 2021","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2507.01903","last_updated":"2025-08-05T16:19:40Z","snapshot_observed_at":"2026-08-07T12:18:28.218519Z","submitted_at":"2025-07-02T17:19:20Z","title":"AI4Research: A Survey of Artificial Intelligence for Scientific Research","version":2},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-06T20:45:09.686769Z"},"links":{"citing_paper":"/paper/2507.01903"},"observation_digest":"sha256:8e14943d0ac601e01d391d1ca46f6f3fda4d9a4be2c792f6aa430c793b38dd1e","observation_id":"e8fc25d1-5ffa-40cd-ab6e-1f47f6f0a665","resolution":{"observed_at":"2026-08-06T20:45:09.686769Z","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":"2026-08-06T20:45:09.793970Z","title":"Homogenization effects of large language models on human creative ideation","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.01903","last_updated":"2025-08-05T16:19:40Z","snapshot_observed_at":"2026-08-07T12:18:28.218519Z","submitted_at":"2025-07-02T17:19:20Z","title":"AI4Research: A Survey of Artificial Intelligence for Scientific Research","version":2},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-06T20:45:09.793970Z"},"links":{"citing_paper":"/paper/2507.01903"},"observation_digest":"sha256:12569709971bba2c074bb9248b62c8c4f21d3064e512e800270f015245acea1e","observation_id":"ed790ee5-f444-4c72-9568-4dac00e88cf1","resolution":{"observed_at":"2026-08-06T20:45:09.793970Z","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":"2026-08-06T20:45:09.898489Z","title":"Closed-loop transfer enables artificial intelligence to yield chemical knowledge.Nature, 633(8029):351–358, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.01903","last_updated":"2025-08-05T16:19:40Z","snapshot_observed_at":"2026-08-07T12:18:28.218519Z","submitted_at":"2025-07-02T17:19:20Z","title":"AI4Research: A Survey of Artificial Intelligence for Scientific Research","version":2},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-08-06T20:45:09.898489Z"},"links":{"citing_paper":"/paper/2507.01903"},"observation_digest":"sha256:7a04b8c974983d3304e135014cd85202f7f17f5248ef8298674fff879749b367","observation_id":"e29cf172-9027-42fa-90d8-3f086637ae31","resolution":{"observed_at":"2026-08-06T20:45:09.898489Z","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":"2026-08-06T20:45:09.980076Z","title":"Transforming science labs into automated factories of discovery.Science Robotics, 9(95):eadm6991, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.01903","last_updated":"2025-08-05T16:19:40Z","snapshot_observed_at":"2026-08-07T12:18:28.218519Z","submitted_at":"2025-07-02T17:19:20Z","title":"AI4Research: A Survey of Artificial Intelligence for Scientific Research","version":2},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-06T20:45:09.980076Z"},"links":{"citing_paper":"/paper/2507.01903"},"observation_digest":"sha256:5ae7281a5b534d5ad1ff7ab9628bd4654f518f871b326cfc49898ba7e97b2c98","observation_id":"e8a2fc89-4dc0-407c-ba78-cdac8b87d324","resolution":{"observed_at":"2026-08-06T20:45:09.980076Z","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":"2026-08-06T20:45:10.082498Z","title":"The claude 3 model family: Opus, sonnet, haiku","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.01903","last_updated":"2025-08-05T16:19:40Z","snapshot_observed_at":"2026-08-07T12:18:28.218519Z","submitted_at":"2025-07-02T17:19:20Z","title":"AI4Research: A Survey of Artificial Intelligence for Scientific Research","version":2},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-08-06T20:45:10.082498Z"},"links":{"citing_paper":"/paper/2507.01903"},"observation_digest":"sha256:ec3b92ba5de650ab1e0f340e629a0e4cc4dd4372ef1f03db25fb0743d59889fa","observation_id":"40c714d2-c8ce-4f20-9a8e-67c838140378","resolution":{"observed_at":"2026-08-06T20:45:10.082498Z","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":"2026-08-06T20:45:10.140193Z","title":"Meta-designing quantum experiments with language models.arXiv preprint arXiv:2406.02470, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.01903","last_updated":"2025-08-05T16:19:40Z","snapshot_observed_at":"2026-08-07T12:18:28.218519Z","submitted_at":"2025-07-02T17:19:20Z","title":"AI4Research: A Survey of Artificial Intelligence for Scientific Research","version":2},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-06T20:45:10.140193Z"},"links":{"citing_paper":"/paper/2507.01903"},"observation_digest":"sha256:5611a6f6af31a2ea3920fabaa5ef53d95373a9c5bee0d4ed1d0bc44c7ffc1cfc","observation_id":"c59db5c4-c3cc-4bea-bce1-43b681a7ebf4","resolution":{"observed_at":"2026-08-06T20:45:10.140193Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2411.14199","last_updated":"2024-11-21T15:07:42Z","snapshot_observed_at":"2026-07-06T19:53:47.605701Z","submitted_at":"2024-11-21T15:07:42Z","title":"OpenScholar: Synthesizing Scientific Literature with Retrieval-augmented LMs","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2411.14199","snapshot_observed_at":"2026-08-06T20:45:10.208092Z","title":"Openscholar: Synthesizing scientific literature with retrieval-augmented lms.arXiv preprint arXiv:2411.14199, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.01903","last_updated":"2025-08-05T16:19:40Z","snapshot_observed_at":"2026-08-07T12:18:28.218519Z","submitted_at":"2025-07-02T17:19:20Z","title":"AI4Research: A Survey of Artificial Intelligence for Scientific Research","version":2},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-06T20:45:10.208092Z"},"links":{"cited_paper":"/paper/2411.14199","citing_paper":"/paper/2507.01903"},"observation_digest":"sha256:ce4b3e0e1c7ab1ebe7bd8fbc231cdad769087560c3ec2b2d03112851a10fa878","observation_id":"fd2b0bda-119e-419c-8221-a2c065718981","resolution":{"observed_at":"2026-08-06T20:45:10.208092Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2401.13481","last_updated":"2025-07-31T17:19:39Z","snapshot_observed_at":"2026-08-06T16:08:05.213344Z","submitted_at":"2024-01-24T14:29:39Z","title":"How AI Ideas Affect the Creativity, Diversity, and Evolution of Human Ideas: Evidence From a Large, Dynamic Experiment","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2401.13481","snapshot_observed_at":"2026-08-06T20:45:10.303281Z","title":"How ai ideas affect the creativity, diversity, and evolution of human ideas: evidence from a large, dynamic experiment","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.01903","last_updated":"2025-08-05T16:19:40Z","snapshot_observed_at":"2026-08-07T12:18:28.218519Z","submitted_at":"2025-07-02T17:19:20Z","title":"AI4Research: A Survey of Artificial Intelligence for Scientific Research","version":2},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-06T20:45:10.303281Z"},"links":{"cited_paper":"/paper/2401.13481","citing_paper":"/paper/2507.01903"},"observation_digest":"sha256:bfc97c8806825ef0a883f194958f9e0498b86112550da0a863e54a4c3b0015fb","observation_id":"3ffe2099-e831-497d-919b-7b94979507a7","resolution":{"observed_at":"2026-08-06T20:45:10.303281Z","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":"2026-08-06T20:45:10.398208Z","title":"The mighty torr: A benchmark for table reasoning and robustness.arXiv preprint arXiv:2502.19412, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2507.01903","last_updated":"2025-08-05T16:19:40Z","snapshot_observed_at":"2026-08-07T12:18:28.218519Z","submitted_at":"2025-07-02T17:19:20Z","title":"AI4Research: A Survey of Artificial Intelligence for Scientific Research","version":2},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-08-06T20:45:10.398208Z"},"links":{"citing_paper":"/paper/2507.01903"},"observation_digest":"sha256:b7bc0f3245f59563c735d8a64e336a54d2da2843ce7a06ba82621c60b69fc691","observation_id":"f8a9470d-b0a1-48dc-a45f-9aabb4f8d8c8","resolution":{"observed_at":"2026-08-06T20:45:10.398208Z","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":"2026-08-06T20:45:10.495313Z","title":"gpt-researcher, May 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2507.01903","last_updated":"2025-08-05T16:19:40Z","snapshot_observed_at":"2026-08-07T12:18:28.218519Z","submitted_at":"2025-07-02T17:19:20Z","title":"AI4Research: A Survey of Artificial Intelligence for Scientific Research","version":2},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-06T20:45:10.495313Z"},"links":{"citing_paper":"/paper/2507.01903"},"observation_digest":"sha256:2a41b4ff993a442d0cf0443c89a3ca5675be91002d688f214fc7b7a04b7e025c","observation_id":"5ea6e036-c519-490d-929b-893809f30fbb","resolution":{"observed_at":"2026-08-06T20:45:10.495313Z","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":"2026-08-06T20:45:10.586110Z","title":"Generating fact checking explanations","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.01903","last_updated":"2025-08-05T16:19:40Z","snapshot_observed_at":"2026-08-07T12:18:28.218519Z","submitted_at":"2025-07-02T17:19:20Z","title":"AI4Research: A Survey of Artificial Intelligence for Scientific Research","version":2},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-06T20:45:10.586110Z"},"links":{"citing_paper":"/paper/2507.01903"},"observation_digest":"sha256:5a2b76fd973f2393986a64c382170b814c6e5be7563a9c40ea63346dc454f012","observation_id":"acfbdcb3-42e8-40f7-b17c-c87b0678b6de","resolution":{"observed_at":"2026-08-06T20:45:10.586110Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2501.02157","last_updated":"2025-05-31T06:33:39Z","snapshot_observed_at":"2026-07-06T20:16:27.318761Z","submitted_at":"2025-01-04T01:46:49Z","title":"Personalized Graph-Based Retrieval for Large Language Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2501.02157","snapshot_observed_at":"2026-08-06T20:45:10.649443Z","title":"Personalized graph-based retrieval for large language models.arXiv preprint arXiv:2501.02157, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2507.01903","last_updated":"2025-08-05T16:19:40Z","snapshot_observed_at":"2026-08-07T12:18:28.218519Z","submitted_at":"2025-07-02T17:19:20Z","title":"AI4Research: A Survey of Artificial Intelligence for Scientific Research","version":2},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-06T20:45:10.649443Z"},"links":{"cited_paper":"/paper/2501.02157","citing_paper":"/paper/2507.01903"},"observation_digest":"sha256:0dbee02339832c124eb54036160cecfa0baf23993d3d0d20f2a9dddee4a01295","observation_id":"b186187c-6137-4b49-b7b8-ac6079f44b28","resolution":{"observed_at":"2026-08-06T20:45:10.649443Z","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":"2026-08-06T20:45:10.724144Z","title":"The sciqa scientific question answering benchmark for scholarly knowledge.Scientific Reports, 13(1):7240, May 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2507.01903","last_updated":"2025-08-05T16:19:40Z","snapshot_observed_at":"2026-08-07T12:18:28.218519Z","submitted_at":"2025-07-02T17:19:20Z","title":"AI4Research: A Survey of Artificial Intelligence for Scientific Research","version":2},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-06T20:45:10.724144Z"},"links":{"citing_paper":"/paper/2507.01903"},"observation_digest":"sha256:6fe6deff9a6d536f9634cf84b9371ff0536ddbcef7d4e89ea07836fc3c0c1276","observation_id":"8e210afe-ad7c-44a8-8454-c0179e633ce7","resolution":{"observed_at":"2026-08-06T20:45:10.724144Z","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":"2026-08-06T20:45:10.827319Z","title":"Self-driving labs are the new ai asset.Axios, Aug 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.01903","last_updated":"2025-08-05T16:19:40Z","snapshot_observed_at":"2026-08-07T12:18:28.218519Z","submitted_at":"2025-07-02T17:19:20Z","title":"AI4Research: A Survey of Artificial Intelligence for Scientific Research","version":2},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-06T20:45:10.827319Z"},"links":{"citing_paper":"/paper/2507.01903"},"observation_digest":"sha256:162d9077b55f1bafd7e728d99021e5e4781ce81fd8c37642a2401697747e3d3d","observation_id":"907e7f42-35fe-4554-a1c7-b40bcc3f5cb4","resolution":{"observed_at":"2026-08-06T20:45:10.827319Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2412.18781","last_updated":"2025-07-18T08:42:53Z","snapshot_observed_at":"2026-08-03T09:01:42.530948Z","submitted_at":"2024-12-25T05:02:22Z","title":"Robustness Evaluation of Offline Reinforcement Learning for Robot Control Against Action Perturbations","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2412.18781","snapshot_observed_at":"2026-08-06T20:45:10.897118Z","title":"Robustness evaluation of offline reinforcement learning for robot control against action perturbations.arXiv preprint arXiv:2412.18781, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.01903","last_updated":"2025-08-05T16:19:40Z","snapshot_observed_at":"2026-08-07T12:18:28.218519Z","submitted_at":"2025-07-02T17:19:20Z","title":"AI4Research: A Survey of Artificial Intelligence for Scientific Research","version":2},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-06T20:45:10.897118Z"},"links":{"cited_paper":"/paper/2412.18781","citing_paper":"/paper/2507.01903"},"observation_digest":"sha256:b71e620533f5177449592a5d0e6d1ae0c3435ea33d11d138768e2c7fcc71e4e6","observation_id":"314eadd0-6470-45e6-aa10-6fce5f7c267b","resolution":{"observed_at":"2026-08-06T20:45:10.897118Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2503.16561","last_updated":"2025-09-04T08:12:41Z","snapshot_observed_at":"2026-08-07T16:50:00.813935Z","submitted_at":"2025-03-20T06:14:02Z","title":"FutureGen: A RAG-based Approach to Generate the Future Work of Scientific Article","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2503.16561","snapshot_observed_at":"2026-08-06T20:45:10.976013Z","title":"Futuregen: Llm-rag approach to generate the future work of scientific article.arXiv preprint arXiv:2503.16561, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2507.01903","last_updated":"2025-08-05T16:19:40Z","snapshot_observed_at":"2026-08-07T12:18:28.218519Z","submitted_at":"2025-07-02T17:19:20Z","title":"AI4Research: A Survey of Artificial Intelligence for Scientific Research","version":2},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-06T20:45:10.976013Z"},"links":{"cited_paper":"/paper/2503.16561","citing_paper":"/paper/2507.01903"},"observation_digest":"sha256:de4d3bc9025ccf7edb48818c3cd445fad67b477f041ace4716ba96e5264fe935","observation_id":"45d8570e-7e26-4f1f-bf22-48533e34f336","resolution":{"observed_at":"2026-08-06T20:45:10.976013Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2404.07738","last_updated":"2025-02-09T08:15:44Z","snapshot_observed_at":"2026-07-06T17:58:52.016903Z","submitted_at":"2024-04-11T13:36:29Z","title":"ResearchAgent: Iterative Research Idea Generation over Scientific Literature with Large Language Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.07738","snapshot_observed_at":"2026-08-06T20:45:11.051532Z","title":"Researchagent: Itera- tive research idea generation over scientific literature with large language models.arXiv preprint arXiv:2404.07738, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.01903","last_updated":"2025-08-05T16:19:40Z","snapshot_observed_at":"2026-08-07T12:18:28.218519Z","submitted_at":"2025-07-02T17:19:20Z","title":"AI4Research: A Survey of Artificial Intelligence for Scientific Research","version":2},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-06T20:45:11.051532Z"},"links":{"cited_paper":"/paper/2404.07738","citing_paper":"/paper/2507.01903"},"observation_digest":"sha256:d56753410a372bcc2952f378541619af8689e2118348b3b33d04e3dfd45a0b8e","observation_id":"bb9d71d1-26b9-4063-848b-5ea3ee9d38c3","resolution":{"observed_at":"2026-08-06T20:45:11.051532Z","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":"2026-08-06T20:45:11.100607Z","title":"Scientific paper recommendation: A survey.Ieee Access, 7:9324–9339, Jan 2019","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2507.01903","last_updated":"2025-08-05T16:19:40Z","snapshot_observed_at":"2026-08-07T12:18:28.218519Z","submitted_at":"2025-07-02T17:19:20Z","title":"AI4Research: A Survey of Artificial Intelligence for Scientific Research","version":2},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-06T20:45:11.100607Z"},"links":{"citing_paper":"/paper/2507.01903"},"observation_digest":"sha256:0a70b4eb535bdd4ec3b7f551f125b9aaabaef06d6ba20b8f7215911865d57e39","observation_id":"70a0ba15-bdd4-4343-a3fb-8633f96195bc","resolution":{"observed_at":"2026-08-06T20:45:11.100607Z","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":"2026-08-06T20:45:11.161131Z","title":"Language models surface the unwritten code of science and society.arXiv preprint arXiv:2505.18942, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2507.01903","last_updated":"2025-08-05T16:19:40Z","snapshot_observed_at":"2026-08-07T12:18:28.218519Z","submitted_at":"2025-07-02T17:19:20Z","title":"AI4Research: A Survey of Artificial Intelligence for Scientific Research","version":2},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-06T20:45:11.161131Z"},"links":{"citing_paper":"/paper/2507.01903"},"observation_digest":"sha256:9b41a919f3254cc4acd23dce6e2204b338d1c7ea8449f7efa7a3b47e0ece45c4","observation_id":"375c5f7b-4f7a-464d-ab5e-3c5406eca6b9","resolution":{"observed_at":"2026-08-06T20:45:11.161131Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2411.13902","last_updated":"2024-11-21T07:28:07Z","snapshot_observed_at":"2026-08-07T20:47:18.184292Z","submitted_at":"2024-11-21T07:28:07Z","title":"PIORS: Personalized Intelligent Outpatient Reception based on Large Language Model with Multi-Agents Medical Scenario Simulation","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2411.13902","snapshot_observed_at":"2026-08-06T20:45:11.241798Z","title":"Piors: Personalized intelligent outpatient reception based on large language model with multi-agents medical scenario simulation.arXiv preprint arXiv:2411.13902, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.01903","last_updated":"2025-08-05T16:19:40Z","snapshot_observed_at":"2026-08-07T12:18:28.218519Z","submitted_at":"2025-07-02T17:19:20Z","title":"AI4Research: A Survey of Artificial Intelligence for Scientific Research","version":2},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-06T20:45:11.241798Z"},"links":{"cited_paper":"/paper/2411.13902","citing_paper":"/paper/2507.01903"},"observation_digest":"sha256:60b19e1dfe70b106967132907dee4f2d0a91550f6d28ff1932094016d62a2cbd","observation_id":"fa11f825-0aa5-4115-a0bb-298bf0f02967","resolution":{"observed_at":"2026-08-06T20:45:11.241798Z","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":"2026-08-06T20:45:11.287729Z","title":"Automated machine learning: past, present and future.Artificial intelligence review, 57(5): 122, Apr 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.01903","last_updated":"2025-08-05T16:19:40Z","snapshot_observed_at":"2026-08-07T12:18:28.218519Z","submitted_at":"2025-07-02T17:19:20Z","title":"AI4Research: A Survey of Artificial Intelligence for Scientific Research","version":2},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-06T20:45:11.287729Z"},"links":{"citing_paper":"/paper/2507.01903"},"observation_digest":"sha256:c5a7adf42acd9b9a59b2f0359628229beb3821436c6beabcbe040e7efea55615","observation_id":"ba13a334-8f2e-41d3-a208-3cc95def2b9a","resolution":{"observed_at":"2026-08-06T20:45:11.287729Z","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":"2026-08-06T20:45:11.345773Z","title":"Google deepmind’s ai dreamed up 380,000 new materials","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2507.01903","last_updated":"2025-08-05T16:19:40Z","snapshot_observed_at":"2026-08-07T12:18:28.218519Z","submitted_at":"2025-07-02T17:19:20Z","title":"AI4Research: A Survey of Artificial Intelligence for Scientific Research","version":2},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-06T20:45:11.345773Z"},"links":{"citing_paper":"/paper/2507.01903"},"observation_digest":"sha256:1f92acd8d82a18dcfee8e3cfcd0224522a11259bb181a6df533896caaf45b4dd","observation_id":"44076d83-21b1-42fd-bc4d-f91ffa0ae904","resolution":{"observed_at":"2026-08-06T20:45:11.345773Z","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":"2026-08-06T20:45:11.404239Z","title":"Eight years of automl: categorisation, review and trends.Knowledge and Information Systems, 65(12):5097–5149, Aug 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2507.01903","last_updated":"2025-08-05T16:19:40Z","snapshot_observed_at":"2026-08-07T12:18:28.218519Z","submitted_at":"2025-07-02T17:19:20Z","title":"AI4Research: A Survey of Artificial Intelligence for Scientific Research","version":2},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-08-06T20:45:11.404239Z"},"links":{"citing_paper":"/paper/2507.01903"},"observation_digest":"sha256:1f5949cdc8933371eb20942aa0f211491571b90475c966253906bef157f26ba7","observation_id":"928df020-7734-48d8-ab10-5c040650a058","resolution":{"observed_at":"2026-08-06T20:45:11.404239Z","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":"2026-08-06T20:45:11.502116Z","title":"Large physics models: Towards a collaborative approach with large language models and foundation models.arXiv preprint arXiv:2501.05382, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2507.01903","last_updated":"2025-08-05T16:19:40Z","snapshot_observed_at":"2026-08-07T12:18:28.218519Z","submitted_at":"2025-07-02T17:19:20Z","title":"AI4Research: A Survey of Artificial Intelligence for Scientific Research","version":2},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-06T20:45:11.502116Z"},"links":{"citing_paper":"/paper/2507.01903"},"observation_digest":"sha256:4eb9a91b2ce63f3039cac7f43338ebcc6b3072a974bc03961ffa227265c884db","observation_id":"a9783f92-13f6-49f1-b3ae-81e8e5584b55","resolution":{"observed_at":"2026-08-06T20:45:11.502116Z","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":"2026-08-06T20:45:11.560907Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.01903","last_updated":"2025-08-05T16:19:40Z","snapshot_observed_at":"2026-08-07T12:18:28.218519Z","submitted_at":"2025-07-02T17:19:20Z","title":"AI4Research: A Survey of Artificial Intelligence for Scientific Research","version":2},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-06T20:45:11.560907Z"},"links":{"citing_paper":"/paper/2507.01903"},"observation_digest":"sha256:3976dcbcb97159b83af2e172dcc58afba520ca27a921bd63583fd164e569f923","observation_id":"0b50a237-6426-4a8b-81d8-bcaa19dbdbd4","resolution":{"observed_at":"2026-08-06T20:45:11.560907Z","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":"2026-08-06T20:45:11.662479Z","title":"The quality assist: A technology-assisted peer review based on citation functions to predict the paper quality.IEEE Access, 10:126815–126831, Dec 2022","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2507.01903","last_updated":"2025-08-05T16:19:40Z","snapshot_observed_at":"2026-08-07T12:18:28.218519Z","submitted_at":"2025-07-02T17:19:20Z","title":"AI4Research: A Survey of Artificial Intelligence for Scientific Research","version":2},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-06T20:45:11.662479Z"},"links":{"citing_paper":"/paper/2507.01903"},"observation_digest":"sha256:7875a20807e36385f1131c88fee1c0c41b8c190d50357d0cbefd0a66193daa67","observation_id":"41e1c666-62f1-42e2-9bac-9bfdfb0b0813","resolution":{"observed_at":"2026-08-06T20:45:11.662479Z","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":"2026-08-06T20:45:11.727488Z","title":null,"venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2507.01903","last_updated":"2025-08-05T16:19:40Z","snapshot_observed_at":"2026-08-07T12:18:28.218519Z","submitted_at":"2025-07-02T17:19:20Z","title":"AI4Research: A Survey of Artificial Intelligence for Scientific Research","version":2},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-06T20:45:11.727488Z"},"links":{"citing_paper":"/paper/2507.01903"},"observation_digest":"sha256:851c762b3a44d2ddf33a29379639b243f55903dbcdb2cf79482df257b2b2503c","observation_id":"0e933133-799f-4c74-975f-cae43f2cbbe2","resolution":{"observed_at":"2026-08-06T20:45:11.727488Z","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":"2026-08-06T20:45:11.822349Z","title":"Interaction networks for learning about objects, relations and physics.Advances in Neural Information Processing Systems, 29, Dec 2016","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2507.01903","last_updated":"2025-08-05T16:19:40Z","snapshot_observed_at":"2026-08-07T12:18:28.218519Z","submitted_at":"2025-07-02T17:19:20Z","title":"AI4Research: A Survey of Artificial Intelligence for Scientific Research","version":2},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-08-06T20:45:11.822349Z"},"links":{"citing_paper":"/paper/2507.01903"},"observation_digest":"sha256:4f6e4fbf12a09a431752f91dd7921ec29b76ec815a5d0561e0f05b8bce756801","observation_id":"7a35d9e5-405f-463a-a109-cae725792748","resolution":{"observed_at":"2026-08-06T20:45:11.822349Z","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":"2026-08-06T20:45:11.876013Z","title":"Peerqa: A scientific question answering dataset from peer reviews","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2507.01903","last_updated":"2025-08-05T16:19:40Z","snapshot_observed_at":"2026-08-07T12:18:28.218519Z","submitted_at":"2025-07-02T17:19:20Z","title":"AI4Research: A Survey of Artificial Intelligence for Scientific Research","version":2},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-08-06T20:45:11.876013Z"},"links":{"citing_paper":"/paper/2507.01903"},"observation_digest":"sha256:392e0e1395a21a42ef0201ce36601b34cda8301f93545142a475ed245fdd826b","observation_id":"59dfaefd-a5ad-4f56-aa24-848a0e45b5c2","resolution":{"observed_at":"2026-08-06T20:45:11.876013Z","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":"2026-08-06T20:45:12.001326Z","title":"Toward machine learning optimization of experimental design.Nuclear Physics News, 31(1):25–28, Feb 2021","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2507.01903","last_updated":"2025-08-05T16:19:40Z","snapshot_observed_at":"2026-08-07T12:18:28.218519Z","submitted_at":"2025-07-02T17:19:20Z","title":"AI4Research: A Survey of Artificial Intelligence for Scientific Research","version":2},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-08-06T20:45:12.001326Z"},"links":{"citing_paper":"/paper/2507.01903"},"observation_digest":"sha256:152d7095af7f563d714a0eb7956c1fe66a83fd6ddea087e033aac558ea110e0c","observation_id":"e6f0b10f-748a-407e-82d4-028cb1e307f6","resolution":{"observed_at":"2026-08-06T20:45:12.001326Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2309.16540","last_updated":"2024-03-06T20:12:01Z","snapshot_observed_at":"2026-07-06T16:25:01.609308Z","submitted_at":"2023-09-28T15:53:44Z","title":"Unsupervised Pretraining for Fact Verification by Language Model Distillation","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2309.16540","snapshot_observed_at":"2026-08-06T20:45:12.004875Z","title":"Unsupervisedpretrainingforfactverificationbylanguage model distillation.arXiv preprint arXiv:2309.16540, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2507.01903","last_updated":"2025-08-05T16:19:40Z","snapshot_observed_at":"2026-08-07T12:18:28.218519Z","submitted_at":"2025-07-02T17:19:20Z","title":"AI4Research: A Survey of Artificial Intelligence for Scientific Research","version":2},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-08-06T20:45:12.004875Z"},"links":{"cited_paper":"/paper/2309.16540","citing_paper":"/paper/2507.01903"},"observation_digest":"sha256:816c6868533287dc5354707802f355075da7c0a9b03ff2ce8114f893de828514","observation_id":"acbdeef6-d873-43ba-8f81-f38dd38d785e","resolution":{"observed_at":"2026-08-06T20:45:12.004875Z","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":"2026-08-06T20:45:12.062688Z","title":"Agentichypothesis: A survey on hypothesis generation using llm systems","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2507.01903","last_updated":"2025-08-05T16:19:40Z","snapshot_observed_at":"2026-08-07T12:18:28.218519Z","submitted_at":"2025-07-02T17:19:20Z","title":"AI4Research: A Survey of Artificial Intelligence for Scientific Research","version":2},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-08-06T20:45:12.062688Z"},"links":{"citing_paper":"/paper/2507.01903"},"observation_digest":"sha256:0ecf9b13b0903f2d693f3b95bf9de8e434cf62a33e0831b486c1d24367ba068d","observation_id":"4efc13c6-b93d-4783-a781-092112db554c","resolution":{"observed_at":"2026-08-06T20:45:12.062688Z","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":"2026-08-06T20:45:12.068493Z","title":"Paper recommender systems: a literature survey.International Journal on Digital Libraries, 17(4):305–338, Jul 2016","venue":null,"work_id":null,"year":2016},"citing_paper":{"arxiv_id":"2507.01903","last_updated":"2025-08-05T16:19:40Z","snapshot_observed_at":"2026-08-07T12:18:28.218519Z","submitted_at":"2025-07-02T17:19:20Z","title":"AI4Research: A Survey of Artificial Intelligence for Scientific Research","version":2},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-08-06T20:45:12.068493Z"},"links":{"citing_paper":"/paper/2507.01903"},"observation_digest":"sha256:613cfdd1a100be38edbda921df03f8c89beb27d01326682d1a6315fcb399f484","observation_id":"67981155-16f8-49a4-904b-8f63bc8a2368","resolution":{"observed_at":"2026-08-06T20:45:12.068493Z","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":"2026-08-06T20:45:12.071666Z","title":null,"venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2507.01903","last_updated":"2025-08-05T16:19:40Z","snapshot_observed_at":"2026-08-07T12:18:28.218519Z","submitted_at":"2025-07-02T17:19:20Z","title":"AI4Research: A Survey of Artificial Intelligence for Scientific Research","version":2},"reference_index":53,"source":"pdf_text","source_observed_at":"2026-08-06T20:45:12.071666Z"},"links":{"citing_paper":"/paper/2507.01903"},"observation_digest":"sha256:b28c99c2dc536b4038b41d9269634a4d476b628976cd7ed309209d8c3aa6ab09","observation_id":"d50725b8-065f-4f9f-b93e-0fe563c0e17d","resolution":{"observed_at":"2026-08-06T20:45:12.071666Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2310.00367","last_updated":"2024-01-23T15:20:33Z","snapshot_observed_at":"2026-08-05T10:35:16.985181Z","submitted_at":"2023-09-30T13:15:49Z","title":"AutomaTikZ: Text-Guided Synthesis of Scientific Vector Graphics with TikZ","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2310.00367","snapshot_observed_at":"2026-08-06T20:45:12.074741Z","title":"Automatikz: Text-guided synthesis of scientific vector graphics with tikz.arXiv preprint arXiv:2310.00367, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2507.01903","last_updated":"2025-08-05T16:19:40Z","snapshot_observed_at":"2026-08-07T12:18:28.218519Z","submitted_at":"2025-07-02T17:19:20Z","title":"AI4Research: A Survey of Artificial Intelligence for Scientific Research","version":2},"reference_index":54,"source":"pdf_text","source_observed_at":"2026-08-06T20:45:12.074741Z"},"links":{"cited_paper":"/paper/2310.00367","citing_paper":"/paper/2507.01903"},"observation_digest":"sha256:71660373362b1f15c49bab407ce6d3f16643118709bcffec5519491488db2999","observation_id":"21b5d960-b176-4e3d-b3da-74047b98e1bc","resolution":{"observed_at":"2026-08-06T20:45:12.074741Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2503.11509","last_updated":"2025-08-14T08:52:03Z","snapshot_observed_at":"2026-08-07T17:03:37.792481Z","submitted_at":"2025-03-14T15:29:58Z","title":"TikZero: Zero-Shot Text-Guided Graphics Program Synthesis","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2503.11509","snapshot_observed_at":"2026-08-06T20:45:12.078182Z","title":"Tikzero: Zero-shot text-guided graphics program synthesis.arXiv preprint arXiv:2503.11509, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2507.01903","last_updated":"2025-08-05T16:19:40Z","snapshot_observed_at":"2026-08-07T12:18:28.218519Z","submitted_at":"2025-07-02T17:19:20Z","title":"AI4Research: A Survey of Artificial Intelligence for Scientific Research","version":2},"reference_index":55,"source":"pdf_text","source_observed_at":"2026-08-06T20:45:12.078182Z"},"links":{"cited_paper":"/paper/2503.11509","citing_paper":"/paper/2507.01903"},"observation_digest":"sha256:ccc5268991a9b8f58b3551f8aa8c1a1f7140dd6aed57ef5a4481400c796437a6","observation_id":"0d8525da-49c6-4f42-9f0e-d4a13ede382d","resolution":{"observed_at":"2026-08-06T20:45:12.078182Z","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":"2026-08-06T20:45:12.082273Z","title":"SciBERT: A pretrained language model for scientific text","venue":null,"work_id":null,"year":2019},"citing_paper":{"arxiv_id":"2507.01903","last_updated":"2025-08-05T16:19:40Z","snapshot_observed_at":"2026-08-07T12:18:28.218519Z","submitted_at":"2025-07-02T17:19:20Z","title":"AI4Research: A Survey of Artificial Intelligence for Scientific Research","version":2},"reference_index":56,"source":"pdf_text","source_observed_at":"2026-08-06T20:45:12.082273Z"},"links":{"citing_paper":"/paper/2507.01903"},"observation_digest":"sha256:26af6040be2030c5cdf85ded5d307a247ac65d6521542ba1de8112518ee43d17","observation_id":"88909ae5-f826-4827-8843-1238efe7c588","resolution":{"observed_at":"2026-08-06T20:45:12.082273Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2404.14082","last_updated":"2024-08-23T23:02:28Z","snapshot_observed_at":"2026-07-06T18:03:38.397804Z","submitted_at":"2024-04-22T11:01:51Z","title":"Mechanistic Interpretability for AI Safety -- A Review","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.14082","snapshot_observed_at":"2026-08-06T20:45:12.088952Z","title":"Mechanistic interpretability for ai safety–a review.arXiv preprint arXiv:2404.14082, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.01903","last_updated":"2025-08-05T16:19:40Z","snapshot_observed_at":"2026-08-07T12:18:28.218519Z","submitted_at":"2025-07-02T17:19:20Z","title":"AI4Research: A Survey of Artificial Intelligence for Scientific Research","version":2},"reference_index":57,"source":"pdf_text","source_observed_at":"2026-08-06T20:45:12.088952Z"},"links":{"cited_paper":"/paper/2404.14082","citing_paper":"/paper/2507.01903"},"observation_digest":"sha256:d0d660f00870446abb8857b5f0fe3c87e0544ea6210b9e4c0747e65898c8b83b","observation_id":"aaea465e-4041-487e-aad7-b00352f4157a","resolution":{"observed_at":"2026-08-06T20:45:12.088952Z","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":"10.1145/3702639","metadata_source":"doi_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-06T20:45:13.087964Z","title":"When automated assessment meets automated content generation: Examining text quality in the era of gpts.ACM Trans","venue":null,"work_id":"7edd8096-321f-451f-9141-5979b72e4098","year":2025},"citing_paper":{"arxiv_id":"2507.01903","last_updated":"2025-08-05T16:19:40Z","snapshot_observed_at":"2026-08-07T12:18:28.218519Z","submitted_at":"2025-07-02T17:19:20Z","title":"AI4Research: A Survey of Artificial Intelligence for Scientific Research","version":2},"reference_index":58,"source":"pdf_text","source_observed_at":"2026-08-06T20:45:12.093202Z"},"links":{"citing_paper":"/paper/2507.01903"},"observation_digest":"sha256:a8419ac494a7650cf337f52535ab08cc86e485018b994ceaf1b8e5dfe1dafc70","observation_id":"64bf80b0-9695-4526-9fd0-abf2b7c6476d","resolution":{"observed_at":"2026-08-06T20:45:13.093638Z","resolver_source":"doi","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+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":"2026-08-06T20:45:12.096558Z","title":"Peerassist: leveraging on paper-review interactions to predict peer review decisions","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2507.01903","last_updated":"2025-08-05T16:19:40Z","snapshot_observed_at":"2026-08-07T12:18:28.218519Z","submitted_at":"2025-07-02T17:19:20Z","title":"AI4Research: A Survey of Artificial Intelligence for Scientific Research","version":2},"reference_index":59,"source":"pdf_text","source_observed_at":"2026-08-06T20:45:12.096558Z"},"links":{"citing_paper":"/paper/2507.01903"},"observation_digest":"sha256:784bcd4707e7f5a5ff7381cc43acc442d1921731321390b3907f566a3d487bc7","observation_id":"1db58fb3-ca47-4278-b5c5-0b4063e56b64","resolution":{"observed_at":"2026-08-06T20:45:12.096558Z","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":"2026-08-06T20:45:12.099707Z","title":"Politepeer: does peer review hurt? a dataset to gauge politeness intensity in the peer reviews.Language Resources and Evaluation, 58(4):1291–1313, May 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.01903","last_updated":"2025-08-05T16:19:40Z","snapshot_observed_at":"2026-08-07T12:18:28.218519Z","submitted_at":"2025-07-02T17:19:20Z","title":"AI4Research: A Survey of Artificial Intelligence for Scientific Research","version":2},"reference_index":60,"source":"pdf_text","source_observed_at":"2026-08-06T20:45:12.099707Z"},"links":{"citing_paper":"/paper/2507.01903"},"observation_digest":"sha256:6948ac879cf9d254b2be5b72eb33d603af2cae674a056a72f399f658cc2ad880","observation_id":"8ce1105b-7c8a-4d4a-8681-56d8e6537ea7","resolution":{"observed_at":"2026-08-06T20:45:12.099707Z","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":"2026-08-06T20:45:12.102945Z","title":"General- purpose pre-trained large cellular models for single-cell transcriptomics.National Science Review, 11 (11):nwae340, Sep 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.01903","last_updated":"2025-08-05T16:19:40Z","snapshot_observed_at":"2026-08-07T12:18:28.218519Z","submitted_at":"2025-07-02T17:19:20Z","title":"AI4Research: A Survey of Artificial Intelligence for Scientific Research","version":2},"reference_index":61,"source":"pdf_text","source_observed_at":"2026-08-06T20:45:12.102945Z"},"links":{"citing_paper":"/paper/2507.01903"},"observation_digest":"sha256:783df931c523b97aec1233dcab9eb2dbe818af11dbc3058713fffbeac2a9617b","observation_id":"02ff7f77-20db-4227-a5ed-6704a0765759","resolution":{"observed_at":"2026-08-06T20:45:12.102945Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2311.08896","last_updated":"2024-04-27T12:51:11Z","snapshot_observed_at":"2026-08-06T06:37:58.770756Z","submitted_at":"2023-11-15T12:02:52Z","title":"HeLM: Highlighted Evidence augmented Language Model for Enhanced Table-to-Text Generation","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2311.08896","snapshot_observed_at":"2026-08-06T20:45:12.105888Z","title":"Helm: Highlighted evidence augmented language model for enhanced table-to-text generation.arXiv preprint arXiv:2311.08896, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2507.01903","last_updated":"2025-08-05T16:19:40Z","snapshot_observed_at":"2026-08-07T12:18:28.218519Z","submitted_at":"2025-07-02T17:19:20Z","title":"AI4Research: A Survey of Artificial Intelligence for Scientific Research","version":2},"reference_index":62,"source":"pdf_text","source_observed_at":"2026-08-06T20:45:12.105888Z"},"links":{"cited_paper":"/paper/2311.08896","citing_paper":"/paper/2507.01903"},"observation_digest":"sha256:813c748d641f82c040d3e2c95c6bfa27be7c60fabfa22a03b2a34f6c32e11f46","observation_id":"aa36dab7-b90f-4e51-84d3-aad426ad4557","resolution":{"observed_at":"2026-08-06T20:45:12.105888Z","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":"2026-08-06T20:45:12.109472Z","title":"Generating accurate and engaging research paper titles using nlp techniques","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2507.01903","last_updated":"2025-08-05T16:19:40Z","snapshot_observed_at":"2026-08-07T12:18:28.218519Z","submitted_at":"2025-07-02T17:19:20Z","title":"AI4Research: A Survey of Artificial Intelligence for Scientific Research","version":2},"reference_index":63,"source":"pdf_text","source_observed_at":"2026-08-06T20:45:12.109472Z"},"links":{"citing_paper":"/paper/2507.01903"},"observation_digest":"sha256:40cc2144d9ed875264cd8d84d55c5cf7fe9773a9e4ed12b4e4baf0c9c8f536fb","observation_id":"f6d3c67c-2ed8-42d7-b5cf-66f8e115de91","resolution":{"observed_at":"2026-08-06T20:45:12.109472Z","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":"2026-08-06T20:45:12.112620Z","title":"Using cognitive psychology to understand gpt-3","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2507.01903","last_updated":"2025-08-05T16:19:40Z","snapshot_observed_at":"2026-08-07T12:18:28.218519Z","submitted_at":"2025-07-02T17:19:20Z","title":"AI4Research: A Survey of Artificial Intelligence for Scientific Research","version":2},"reference_index":64,"source":"pdf_text","source_observed_at":"2026-08-06T20:45:12.112620Z"},"links":{"citing_paper":"/paper/2507.01903"},"observation_digest":"sha256:a5065d993598699e91936c352e4c471b9f408543ec8d4feb07c3b9e069bcb09e","observation_id":"5f58d089-1651-4850-96fd-0364b64730a5","resolution":{"observed_at":"2026-08-06T20:45:12.112620Z","resolver_source":null,"status":"malformed_identifier"},"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":"2026-08-06T20:45:12.115454Z","title":"Designing collaborative intelligence systems for employee-ai service co-production.Journal of Service Research, page 10946705241238751, Mar 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.01903","last_updated":"2025-08-05T16:19:40Z","snapshot_observed_at":"2026-08-07T12:18:28.218519Z","submitted_at":"2025-07-02T17:19:20Z","title":"AI4Research: A Survey of Artificial Intelligence for Scientific Research","version":2},"reference_index":65,"source":"pdf_text","source_observed_at":"2026-08-06T20:45:12.115454Z"},"links":{"citing_paper":"/paper/2507.01903"},"observation_digest":"sha256:49b5b7024e812f7526dbd12ec40aadbc09ba316332f13f68347eb2e60fcec332","observation_id":"2176ba46-9472-4c67-bd93-b0283adb4a4b","resolution":{"observed_at":"2026-08-06T20:45:12.115454Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2411.19732","last_updated":"2024-11-29T14:25:54Z","snapshot_observed_at":"2026-07-06T19:58:57.119904Z","submitted_at":"2024-11-29T14:25:54Z","title":"Improving generalization of robot locomotion policies via Sharpness-Aware Reinforcement Learning","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2411.19732","snapshot_observed_at":"2026-08-06T20:45:12.118469Z","title":"Improving gener- alization of robot locomotion policies via sharpness-aware reinforcement learning.arXiv preprint arXiv:2411.19732, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.01903","last_updated":"2025-08-05T16:19:40Z","snapshot_observed_at":"2026-08-07T12:18:28.218519Z","submitted_at":"2025-07-02T17:19:20Z","title":"AI4Research: A Survey of Artificial Intelligence for Scientific Research","version":2},"reference_index":66,"source":"pdf_text","source_observed_at":"2026-08-06T20:45:12.118469Z"},"links":{"cited_paper":"/paper/2411.19732","citing_paper":"/paper/2507.01903"},"observation_digest":"sha256:0d3d606931a8468f46fab91daa61bed889b7ce843f68eea982f5b4ace948ad19","observation_id":"c54ccec5-d083-4a8f-91d1-1281e659ab9b","resolution":{"observed_at":"2026-08-06T20:45:12.118469Z","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":"2026-08-06T20:45:12.121710Z","title":"Colloquium: Machine learning in nuclear physics.Reviews of modern physics, 94(3):031003, Sep 2022","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2507.01903","last_updated":"2025-08-05T16:19:40Z","snapshot_observed_at":"2026-08-07T12:18:28.218519Z","submitted_at":"2025-07-02T17:19:20Z","title":"AI4Research: A Survey of Artificial Intelligence for Scientific Research","version":2},"reference_index":67,"source":"pdf_text","source_observed_at":"2026-08-06T20:45:12.121710Z"},"links":{"citing_paper":"/paper/2507.01903"},"observation_digest":"sha256:f9e334e22ea508ee5b23da55444073767d5082392d24e1d07928885ee20d13eb","observation_id":"960f17f4-5c87-4480-8bbc-6e9c4981945f","resolution":{"observed_at":"2026-08-06T20:45:12.121710Z","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":"2026-08-06T20:45:12.124660Z","title":"Autonomous chemical research with large language models.Nature, 624(7992):570–578, Dec 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2507.01903","last_updated":"2025-08-05T16:19:40Z","snapshot_observed_at":"2026-08-07T12:18:28.218519Z","submitted_at":"2025-07-02T17:19:20Z","title":"AI4Research: A Survey of Artificial Intelligence for Scientific Research","version":2},"reference_index":68,"source":"pdf_text","source_observed_at":"2026-08-06T20:45:12.124660Z"},"links":{"citing_paper":"/paper/2507.01903"},"observation_digest":"sha256:7f40548fbaffc7f94acf378ee539470fb725c07c271b238880a638ae01daef40","observation_id":"db49f1e7-e74a-439c-9012-68122dc8abbb","resolution":{"observed_at":"2026-08-06T20:45:12.124660Z","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":"2026-08-06T20:45:12.127593Z","title":"Artificial intelligence for literature reviews: Opportunities and challenges.Artificial Intelligence Review, 57(10):259, Aug 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.01903","last_updated":"2025-08-05T16:19:40Z","snapshot_observed_at":"2026-08-07T12:18:28.218519Z","submitted_at":"2025-07-02T17:19:20Z","title":"AI4Research: A Survey of Artificial Intelligence for Scientific Research","version":2},"reference_index":69,"source":"pdf_text","source_observed_at":"2026-08-06T20:45:12.127593Z"},"links":{"citing_paper":"/paper/2507.01903"},"observation_digest":"sha256:c1947ea3c27a05f61e734b29d58ae49d5a04dfbffad4526fe0d14fe69a16f586","observation_id":"2c80b522-a729-41ef-9936-e5bce24c6bfc","resolution":{"observed_at":"2026-08-06T20:45:12.127593Z","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":"2026-08-06T20:45:12.130607Z","title":"A non-factoid question-answering taxonomy","venue":null,"work_id":null,"year":2022},"citing_paper":{"arxiv_id":"2507.01903","last_updated":"2025-08-05T16:19:40Z","snapshot_observed_at":"2026-08-07T12:18:28.218519Z","submitted_at":"2025-07-02T17:19:20Z","title":"AI4Research: A Survey of Artificial Intelligence for Scientific Research","version":2},"reference_index":70,"source":"pdf_text","source_observed_at":"2026-08-06T20:45:12.130607Z"},"links":{"citing_paper":"/paper/2507.01903"},"observation_digest":"sha256:5f15a6a9800356c672c8f6b212cefe72cc12874cac1d32f612d1bf4e4c531a34","observation_id":"e4a1f08d-1170-450d-b9b6-b4143b3aa0c0","resolution":{"observed_at":"2026-08-06T20:45:12.130607Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2403.18421","last_updated":"2024-03-27T10:18:21Z","snapshot_observed_at":"2026-08-07T07:50:55.679613Z","submitted_at":"2024-03-27T10:18:21Z","title":"BioMedLM: A 2.7B Parameter Language Model Trained On Biomedical Text","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2403.18421","snapshot_observed_at":"2026-08-06T20:45:12.133608Z","title":"Biomedlm: A 2.7 b parameter language model trained on biomedical text.arXiv preprint arXiv:2403.18421, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.01903","last_updated":"2025-08-05T16:19:40Z","snapshot_observed_at":"2026-08-07T12:18:28.218519Z","submitted_at":"2025-07-02T17:19:20Z","title":"AI4Research: A Survey of Artificial Intelligence for Scientific Research","version":2},"reference_index":71,"source":"pdf_text","source_observed_at":"2026-08-06T20:45:12.133608Z"},"links":{"cited_paper":"/paper/2403.18421","citing_paper":"/paper/2507.01903"},"observation_digest":"sha256:31df2bacf13fc1421a6529f7a1fd52d6e9e8128e36514769d841998254331d23","observation_id":"cc492815-43f0-428a-816e-f7a4c55ef160","resolution":{"observed_at":"2026-08-06T20:45:12.133608Z","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":"2026-08-06T20:45:12.136794Z","title":"Modest: A dataset for multi domain scientific title generation.Knowledge-Based Systems, page 113557, Jun 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2507.01903","last_updated":"2025-08-05T16:19:40Z","snapshot_observed_at":"2026-08-07T12:18:28.218519Z","submitted_at":"2025-07-02T17:19:20Z","title":"AI4Research: A Survey of Artificial Intelligence for Scientific Research","version":2},"reference_index":72,"source":"pdf_text","source_observed_at":"2026-08-06T20:45:12.136794Z"},"links":{"citing_paper":"/paper/2507.01903"},"observation_digest":"sha256:b67b4e0ce27a4b9d6ddc689fdcedab3de44815740cabf7396bde858600fcdbb0","observation_id":"b84b0e43-4c29-4c01-8d16-4bb603ed81aa","resolution":{"observed_at":"2026-08-06T20:45:12.136794Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1808.09468","last_updated":"2018-08-28T18:03:32Z","snapshot_observed_at":"2026-07-06T06:57:57.583279Z","submitted_at":"2018-08-28T18:03:32Z","title":"Learning To Split and Rephrase From Wikipedia Edit History","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1808.09468","snapshot_observed_at":"2026-08-06T20:45:12.139684Z","title":"Learning to split and rephrase from wikipedia edit history.arXiv preprint arXiv:1808.09468, 2018","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2507.01903","last_updated":"2025-08-05T16:19:40Z","snapshot_observed_at":"2026-08-07T12:18:28.218519Z","submitted_at":"2025-07-02T17:19:20Z","title":"AI4Research: A Survey of Artificial Intelligence for Scientific Research","version":2},"reference_index":73,"source":"pdf_text","source_observed_at":"2026-08-06T20:45:12.139684Z"},"links":{"cited_paper":"/paper/1808.09468","citing_paper":"/paper/2507.01903"},"observation_digest":"sha256:e6d0f0d52062fafdf33039f3759e8f263186d4aa01be44c4da705d9aaa69d726","observation_id":"4584c8c3-7a9a-4de3-8619-37a989012145","resolution":{"observed_at":"2026-08-06T20:45:12.139684Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2404.15923","last_updated":"2024-04-24T15:27:25Z","snapshot_observed_at":"2026-07-06T18:05:03.284784Z","submitted_at":"2024-04-24T15:27:25Z","title":"KGValidator: A Framework for Automatic Validation of Knowledge Graph Construction","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.15923","snapshot_observed_at":"2026-08-06T20:45:12.143051Z","title":"Kgvalidator: A framework for automatic validation of knowledge graph construction","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.01903","last_updated":"2025-08-05T16:19:40Z","snapshot_observed_at":"2026-08-07T12:18:28.218519Z","submitted_at":"2025-07-02T17:19:20Z","title":"AI4Research: A Survey of Artificial Intelligence for Scientific Research","version":2},"reference_index":74,"source":"pdf_text","source_observed_at":"2026-08-06T20:45:12.143051Z"},"links":{"cited_paper":"/paper/2404.15923","citing_paper":"/paper/2507.01903"},"observation_digest":"sha256:a77fa826539584ac699266a4dcc5736fa70b61b8dec76f978708982beb107dbc","observation_id":"4f354bb0-d43d-4552-804c-fdd80618a0a7","resolution":{"observed_at":"2026-08-06T20:45:12.143051Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2412.10510","last_updated":"2025-07-24T14:06:15Z","snapshot_observed_at":"2026-08-06T12:09:56.882107Z","submitted_at":"2024-12-13T19:11:18Z","title":"DEFAME: Dynamic Evidence-based FAct-checking with Multimodal Experts","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2412.10510","snapshot_observed_at":"2026-08-06T20:45:12.146690Z","title":"Defame: Dynamic evidence- based fact-checking with multimodal experts.arXiv preprint arXiv:2412.10510, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.01903","last_updated":"2025-08-05T16:19:40Z","snapshot_observed_at":"2026-08-07T12:18:28.218519Z","submitted_at":"2025-07-02T17:19:20Z","title":"AI4Research: A Survey of Artificial Intelligence for Scientific Research","version":2},"reference_index":75,"source":"pdf_text","source_observed_at":"2026-08-06T20:45:12.146690Z"},"links":{"cited_paper":"/paper/2412.10510","citing_paper":"/paper/2507.01903"},"observation_digest":"sha256:0e01f94481007cd79294e1c0d63e80f19944c1f9d7ffb975d5b66a83dcc26a80","observation_id":"7672ba88-381e-4efd-adab-9aa36fbdd073","resolution":{"observed_at":"2026-08-06T20:45:12.146690Z","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":"2026-08-06T20:45:12.149790Z","title":"Ai driven experiment calibration and control","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.01903","last_updated":"2025-08-05T16:19:40Z","snapshot_observed_at":"2026-08-07T12:18:28.218519Z","submitted_at":"2025-07-02T17:19:20Z","title":"AI4Research: A Survey of Artificial Intelligence for Scientific Research","version":2},"reference_index":76,"source":"pdf_text","source_observed_at":"2026-08-06T20:45:12.149790Z"},"links":{"citing_paper":"/paper/2507.01903"},"observation_digest":"sha256:e13842d185862f5b1f97b4ddd0200dec67cf396f6c0f443322445527ae9cc02a","observation_id":"39182903-86d4-4dd7-84ca-47e55a974bc2","resolution":{"observed_at":"2026-08-06T20:45:12.149790Z","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":"2026-08-06T20:45:12.153290Z","title":"Generative artificial intelligence in anatomic pathology.Archives of Pathology & Laboratory Medicine, Apr 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2507.01903","last_updated":"2025-08-05T16:19:40Z","snapshot_observed_at":"2026-08-07T12:18:28.218519Z","submitted_at":"2025-07-02T17:19:20Z","title":"AI4Research: A Survey of Artificial Intelligence for Scientific Research","version":2},"reference_index":77,"source":"pdf_text","source_observed_at":"2026-08-06T20:45:12.153290Z"},"links":{"citing_paper":"/paper/2507.01903"},"observation_digest":"sha256:41a5b8970c9152ba5c94da82b56759f4e85e1d25ec108a0eae5ec942b002ede5","observation_id":"19e8b081-50e8-40dd-92bc-8287e6e0410d","resolution":{"observed_at":"2026-08-06T20:45:12.153290Z","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":"2026-08-06T20:45:12.156091Z","title":"Closed-loop visuomotor control with generative expectation for robotic manipulation","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.01903","last_updated":"2025-08-05T16:19:40Z","snapshot_observed_at":"2026-08-07T12:18:28.218519Z","submitted_at":"2025-07-02T17:19:20Z","title":"AI4Research: A Survey of Artificial Intelligence for Scientific Research","version":2},"reference_index":78,"source":"pdf_text","source_observed_at":"2026-08-06T20:45:12.156091Z"},"links":{"citing_paper":"/paper/2507.01903"},"observation_digest":"sha256:951d3a57b3db30a0b85c37a3ccf3f1b2cc5b4cfcc4af8a45e84cc8198ea0b20c","observation_id":"8e0b9570-2fde-4b1b-b731-302d2b8946ce","resolution":{"observed_at":"2026-08-06T20:45:12.156091Z","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":"2026-08-06T20:45:12.159114Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.01903","last_updated":"2025-08-05T16:19:40Z","snapshot_observed_at":"2026-08-07T12:18:28.218519Z","submitted_at":"2025-07-02T17:19:20Z","title":"AI4Research: A Survey of Artificial Intelligence for Scientific Research","version":2},"reference_index":79,"source":"pdf_text","source_observed_at":"2026-08-06T20:45:12.159114Z"},"links":{"citing_paper":"/paper/2507.01903"},"observation_digest":"sha256:059f87a134202abea57a8894d2885896a3af6ce82c2133d5720c588a3e77be3b","observation_id":"28846a17-c5ff-4a79-992f-e2a1ed1e8238","resolution":{"observed_at":"2026-08-06T20:45:12.159114Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2502.09242","last_updated":"2025-02-13T11:57:51Z","snapshot_observed_at":"2026-07-06T20:35:58.924339Z","submitted_at":"2025-02-13T11:57:51Z","title":"From large language models to multimodal AI: A scoping review on the potential of generative AI in medicine","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2502.09242","snapshot_observed_at":"2026-08-06T20:45:12.162116Z","title":"From large language models to multimodal ai: A scoping review on the potential of generative ai in medicine","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2507.01903","last_updated":"2025-08-05T16:19:40Z","snapshot_observed_at":"2026-08-07T12:18:28.218519Z","submitted_at":"2025-07-02T17:19:20Z","title":"AI4Research: A Survey of Artificial Intelligence for Scientific Research","version":2},"reference_index":80,"source":"pdf_text","source_observed_at":"2026-08-06T20:45:12.162116Z"},"links":{"cited_paper":"/paper/2502.09242","citing_paper":"/paper/2507.01903"},"observation_digest":"sha256:37e4f7316dd438c6e7c17e992c7746e01fe2990c6ef83561d039e5f52496b841","observation_id":"979029f8-8c07-4744-a1b0-343d1dc1b7a9","resolution":{"observed_at":"2026-08-06T20:45:12.162116Z","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":"2026-08-06T20:45:12.165364Z","title":"How to build the virtual cell with artificial intelligence: Priorities and opportunities.Cell, 187(25):7045–7063, Dec 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.01903","last_updated":"2025-08-05T16:19:40Z","snapshot_observed_at":"2026-08-07T12:18:28.218519Z","submitted_at":"2025-07-02T17:19:20Z","title":"AI4Research: A Survey of Artificial Intelligence for Scientific Research","version":2},"reference_index":81,"source":"pdf_text","source_observed_at":"2026-08-06T20:45:12.165364Z"},"links":{"citing_paper":"/paper/2507.01903"},"observation_digest":"sha256:a6c3018f751d46cfb0d394e2c208328852fdc68289cf6f49bd258d23ef8649bb","observation_id":"bb0146dd-7ec0-4949-aefc-e71cecb7fe12","resolution":{"observed_at":"2026-08-06T20:45:12.165364Z","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":"2026-08-06T20:45:12.168442Z","title":"Microvqa: A multimodal reasoning benchmark for microscopy-based scientific research","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2507.01903","last_updated":"2025-08-05T16:19:40Z","snapshot_observed_at":"2026-08-07T12:18:28.218519Z","submitted_at":"2025-07-02T17:19:20Z","title":"AI4Research: A Survey of Artificial Intelligence for Scientific Research","version":2},"reference_index":82,"source":"pdf_text","source_observed_at":"2026-08-06T20:45:12.168442Z"},"links":{"citing_paper":"/paper/2507.01903"},"observation_digest":"sha256:73fd0bce29787476aec720204847cda865d43b8630dbb5570a9fad16ee31a441","observation_id":"f1c0e0c4-7df4-4089-a53e-465f511348bf","resolution":{"observed_at":"2026-08-06T20:45:12.168442Z","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":"2026-08-06T20:45:12.171222Z","title":"Machine learning for molecular and materials science.Nature, 559(7715):547–555, Jul 2018","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2507.01903","last_updated":"2025-08-05T16:19:40Z","snapshot_observed_at":"2026-08-07T12:18:28.218519Z","submitted_at":"2025-07-02T17:19:20Z","title":"AI4Research: A Survey of Artificial Intelligence for Scientific Research","version":2},"reference_index":83,"source":"pdf_text","source_observed_at":"2026-08-06T20:45:12.171222Z"},"links":{"citing_paper":"/paper/2507.01903"},"observation_digest":"sha256:2e601c410aa8ef3692e7a54affa99c825f8ecabbbafcfd0762344483a7900976","observation_id":"078060a2-979b-4b0b-8b59-d2446322a22c","resolution":{"observed_at":"2026-08-06T20:45:12.171222Z","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":"2026-08-06T20:45:12.174448Z","title":"Modest: A dataset for multi domain scientific title generation.Knowledge-Based Systems, 321:113557, Jun 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2507.01903","last_updated":"2025-08-05T16:19:40Z","snapshot_observed_at":"2026-08-07T12:18:28.218519Z","submitted_at":"2025-07-02T17:19:20Z","title":"AI4Research: A Survey of Artificial Intelligence for Scientific Research","version":2},"reference_index":84,"source":"pdf_text","source_observed_at":"2026-08-06T20:45:12.174448Z"},"links":{"citing_paper":"/paper/2507.01903"},"observation_digest":"sha256:07e8715f48d3f1852436f84f100e956028f6fab77a274b0bb57c7839920635cf","observation_id":"449eacc3-4222-468c-81c6-81ecf4455dcd","resolution":{"observed_at":"2026-08-06T20:45:12.174448Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2308.09381","last_updated":"2024-05-14T07:46:16Z","snapshot_observed_at":"2026-07-06T16:07:33.901446Z","submitted_at":"2023-08-18T08:24:57Z","title":"On Gradient-like Explanation under a Black-box Setting: When Black-box Explanations Become as Good as White-box","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2308.09381","snapshot_observed_at":"2026-08-06T20:45:12.177699Z","title":"On gradient-like explanation under a black-box setting: when black-box explanations become as good as white-box.arXiv preprint arXiv:2308.09381, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2507.01903","last_updated":"2025-08-05T16:19:40Z","snapshot_observed_at":"2026-08-07T12:18:28.218519Z","submitted_at":"2025-07-02T17:19:20Z","title":"AI4Research: A Survey of Artificial Intelligence for Scientific Research","version":2},"reference_index":85,"source":"pdf_text","source_observed_at":"2026-08-06T20:45:12.177699Z"},"links":{"cited_paper":"/paper/2308.09381","citing_paper":"/paper/2507.01903"},"observation_digest":"sha256:828d79f29fb9df8c9d91f6740c1db8a1e987935e5280c55582a8d611d42d8ad8","observation_id":"6f1e1532-e5fb-477a-b0c1-1ffeb9b33bd6","resolution":{"observed_at":"2026-08-06T20:45:12.177699Z","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":"2026-08-06T20:45:12.180864Z","title":null,"venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2507.01903","last_updated":"2025-08-05T16:19:40Z","snapshot_observed_at":"2026-08-07T12:18:28.218519Z","submitted_at":"2025-07-02T17:19:20Z","title":"AI4Research: A Survey of Artificial Intelligence for Scientific Research","version":2},"reference_index":86,"source":"pdf_text","source_observed_at":"2026-08-06T20:45:12.180864Z"},"links":{"citing_paper":"/paper/2507.01903"},"observation_digest":"sha256:12455fed80eb39282617c6de3d855cc150857688db989309d56fb8fb30df24f2","observation_id":"2d773568-d00d-44e9-a632-cf4ed5f68740","resolution":{"observed_at":"2026-08-06T20:45:12.180864Z","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":"2026-08-06T20:45:12.183877Z","title":"Science acceleration and accessibility with self-driving labs.Nature Communications, 16(1):3856, Apr 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2507.01903","last_updated":"2025-08-05T16:19:40Z","snapshot_observed_at":"2026-08-07T12:18:28.218519Z","submitted_at":"2025-07-02T17:19:20Z","title":"AI4Research: A Survey of Artificial Intelligence for Scientific Research","version":2},"reference_index":87,"source":"pdf_text","source_observed_at":"2026-08-06T20:45:12.183877Z"},"links":{"citing_paper":"/paper/2507.01903"},"observation_digest":"sha256:86b2302d332967df9f90a1ff2a7cde1b109cdeca311cbcbdf202b9a93ea34c2a","observation_id":"1c47f7c4-5964-4e62-99b9-97fd11689f18","resolution":{"observed_at":"2026-08-06T20:45:12.183877Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2501.19378","last_updated":"2026-04-15T03:29:38Z","snapshot_observed_at":"2026-07-06T20:29:11.710285Z","submitted_at":"2025-01-31T18:31:31Z","title":"TableMaster: A Recipe to Advance Table Understanding with Language Models","version":6},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2501.19378","snapshot_observed_at":"2026-08-06T20:45:12.186984Z","title":"Tablemaster: A recipe to advance table understanding with language models","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2507.01903","last_updated":"2025-08-05T16:19:40Z","snapshot_observed_at":"2026-08-07T12:18:28.218519Z","submitted_at":"2025-07-02T17:19:20Z","title":"AI4Research: A Survey of Artificial Intelligence for Scientific Research","version":2},"reference_index":88,"source":"pdf_text","source_observed_at":"2026-08-06T20:45:12.186984Z"},"links":{"cited_paper":"/paper/2501.19378","citing_paper":"/paper/2507.01903"},"observation_digest":"sha256:a071b3386363481a628eaee0bf6e5051258c2d2d772f0e516eadaee26b6159ec","observation_id":"de4a9d83-d192-48af-b6b5-08ce96b45ec9","resolution":{"observed_at":"2026-08-06T20:45:12.186984Z","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":"2026-08-06T20:45:12.190274Z","title":"Agents for self-driving laboratories applied to quantum computing","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.01903","last_updated":"2025-08-05T16:19:40Z","snapshot_observed_at":"2026-08-07T12:18:28.218519Z","submitted_at":"2025-07-02T17:19:20Z","title":"AI4Research: A Survey of Artificial Intelligence for Scientific Research","version":2},"reference_index":89,"source":"pdf_text","source_observed_at":"2026-08-06T20:45:12.190274Z"},"links":{"citing_paper":"/paper/2507.01903"},"observation_digest":"sha256:a4cf60fc5bf828f32dd45103d97b557cdb9983ddfae03ce874ff8d0cd484647e","observation_id":"1ec5c3e1-40ed-4190-9263-3dab7a31b980","resolution":{"observed_at":"2026-08-06T20:45:12.190274Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2407.11008","last_updated":"2024-06-25T21:49:21Z","snapshot_observed_at":"2026-08-07T15:21:12.104307Z","submitted_at":"2024-06-25T21:49:21Z","title":"Figuring out Figures: Using Textual References to Caption Scientific Figures","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2407.11008","snapshot_observed_at":"2026-08-06T20:45:12.193370Z","title":"Figuring out figures: Using textual references to caption scientific figures","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.01903","last_updated":"2025-08-05T16:19:40Z","snapshot_observed_at":"2026-08-07T12:18:28.218519Z","submitted_at":"2025-07-02T17:19:20Z","title":"AI4Research: A Survey of Artificial Intelligence for Scientific Research","version":2},"reference_index":90,"source":"pdf_text","source_observed_at":"2026-08-06T20:45:12.193370Z"},"links":{"cited_paper":"/paper/2407.11008","citing_paper":"/paper/2507.01903"},"observation_digest":"sha256:3eac85e1c856dcd0f2056b875f4d49a1106955d09cb3cb4b3c9dab24a5c475aa","observation_id":"c9e28e6f-5077-4f45-903d-492cc7b30824","resolution":{"observed_at":"2026-08-06T20:45:12.193370Z","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":"2026-08-06T20:45:12.196440Z","title":"Can large language models detect misinformation in scientific news reporting?arXiv preprint arXiv:2402.14268, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.01903","last_updated":"2025-08-05T16:19:40Z","snapshot_observed_at":"2026-08-07T12:18:28.218519Z","submitted_at":"2025-07-02T17:19:20Z","title":"AI4Research: A Survey of Artificial Intelligence for Scientific Research","version":2},"reference_index":91,"source":"pdf_text","source_observed_at":"2026-08-06T20:45:12.196440Z"},"links":{"citing_paper":"/paper/2507.01903"},"observation_digest":"sha256:7676e2287c37ae52c990e0ed3ede69603125e82a7c848fb1d1c0e2ebd281baf2","observation_id":"b7203878-2b91-40a4-88ea-189bf9500956","resolution":{"observed_at":"2026-08-06T20:45:12.196440Z","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":"2026-08-06T20:45:12.199698Z","title":"Citebart: Learning to generate citations for local citation recommen- dation","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.01903","last_updated":"2025-08-05T16:19:40Z","snapshot_observed_at":"2026-08-07T12:18:28.218519Z","submitted_at":"2025-07-02T17:19:20Z","title":"AI4Research: A Survey of Artificial Intelligence for Scientific Research","version":2},"reference_index":92,"source":"pdf_text","source_observed_at":"2026-08-06T20:45:12.199698Z"},"links":{"citing_paper":"/paper/2507.01903"},"observation_digest":"sha256:6b9f7c1c6c68738277ef0f5f670f6c85c58bea9f6f0a07db23f8b19ec94ba30f","observation_id":"1601cb18-0a35-406c-a19a-497c74d50618","resolution":{"observed_at":"2026-08-06T20:45:12.199698Z","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":"2026-08-06T20:45:12.203068Z","title":"Art or artifice? large language models and the false promise of creativity","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.01903","last_updated":"2025-08-05T16:19:40Z","snapshot_observed_at":"2026-08-07T12:18:28.218519Z","submitted_at":"2025-07-02T17:19:20Z","title":"AI4Research: A Survey of Artificial Intelligence for Scientific Research","version":2},"reference_index":93,"source":"pdf_text","source_observed_at":"2026-08-06T20:45:12.203068Z"},"links":{"citing_paper":"/paper/2507.01903"},"observation_digest":"sha256:30f5b55ab96ad31063c8d1787c31e7a5cc6bb6c10f089517b19f90b2ffa6f8ca","observation_id":"d1488317-9bc3-44f5-902b-fd06b5f5c364","resolution":{"observed_at":"2026-08-06T20:45:12.203068Z","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":"2026-08-06T20:45:12.206591Z","title":"Automated focused feedback generation for scientific writing assistance","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.01903","last_updated":"2025-08-05T16:19:40Z","snapshot_observed_at":"2026-08-07T12:18:28.218519Z","submitted_at":"2025-07-02T17:19:20Z","title":"AI4Research: A Survey of Artificial Intelligence for Scientific Research","version":2},"reference_index":94,"source":"pdf_text","source_observed_at":"2026-08-06T20:45:12.206591Z"},"links":{"citing_paper":"/paper/2507.01903"},"observation_digest":"sha256:1f6a8a7023adcff6cd6320e472ad479c1cb2c1009bdf041d693a6c742db50e0c","observation_id":"be1cfdb1-e623-470b-90d1-16bbb0ccac06","resolution":{"observed_at":"2026-08-06T20:45:12.206591Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.07095","last_updated":"2025-02-26T11:57:30Z","snapshot_observed_at":"2026-08-06T21:08:58.653035Z","submitted_at":"2024-10-09T17:34:27Z","title":"MLE-bench: Evaluating Machine Learning Agents on Machine Learning Engineering","version":6},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.07095","snapshot_observed_at":"2026-08-06T20:45:12.210151Z","title":"Mle-bench: Evaluating machine learning agents on machine learning engineering.arXiv preprint arXiv:2410.07095, 2024","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2507.01903","last_updated":"2025-08-05T16:19:40Z","snapshot_observed_at":"2026-08-07T12:18:28.218519Z","submitted_at":"2025-07-02T17:19:20Z","title":"AI4Research: A Survey of Artificial Intelligence for Scientific Research","version":2},"reference_index":95,"source":"pdf_text","source_observed_at":"2026-08-06T20:45:12.210151Z"},"links":{"cited_paper":"/paper/2410.07095","citing_paper":"/paper/2507.01903"},"observation_digest":"sha256:da0a17388fa547262d971ac0ea3829242c1b2bba21ae7b23a57959ef4f415061","observation_id":"6fe5516d-1166-42c1-9628-e810171168ca","resolution":{"observed_at":"2026-08-06T20:45:12.210151Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2412.07951","last_updated":"2025-05-29T16:10:25Z","snapshot_observed_at":"2026-07-06T20:04:57.037551Z","submitted_at":"2024-12-10T22:31:29Z","title":"From Lived Experience to Insight: Unpacking the Psychological Risks of Using AI Conversational Agents","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2412.07951","snapshot_observed_at":"2026-08-06T20:45:12.213860Z","title":"From lived experi- ence to insight: Unpacking the psychological risks of using ai conversational agents.arXiv preprint arXiv:2412.07951, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.01903","last_updated":"2025-08-05T16:19:40Z","snapshot_observed_at":"2026-08-07T12:18:28.218519Z","submitted_at":"2025-07-02T17:19:20Z","title":"AI4Research: A Survey of Artificial Intelligence for Scientific Research","version":2},"reference_index":96,"source":"pdf_text","source_observed_at":"2026-08-06T20:45:12.213860Z"},"links":{"cited_paper":"/paper/2412.07951","citing_paper":"/paper/2507.01903"},"observation_digest":"sha256:6a4f488e358538518eda42f8b6a5b1986fdb672d24d92fd4d807cbe767c7643e","observation_id":"e6b190f0-afd2-4e73-9cd9-5dfcc248f75e","resolution":{"observed_at":"2026-08-06T20:45:12.213860Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2505.22126","last_updated":"2025-05-28T08:51:01Z","snapshot_observed_at":"2026-08-07T13:12:16.392134Z","submitted_at":"2025-05-28T08:51:01Z","title":"SridBench: Benchmark of Scientific Research Illustration Drawing of Image Generation Model","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2505.22126","snapshot_observed_at":"2026-08-06T20:45:12.217512Z","title":"Sridbench: Benchmark of scientific research illustration drawing of image generation model.arXiv preprint arXiv:2505.22126, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2507.01903","last_updated":"2025-08-05T16:19:40Z","snapshot_observed_at":"2026-08-07T12:18:28.218519Z","submitted_at":"2025-07-02T17:19:20Z","title":"AI4Research: A Survey of Artificial Intelligence for Scientific Research","version":2},"reference_index":97,"source":"pdf_text","source_observed_at":"2026-08-06T20:45:12.217512Z"},"links":{"cited_paper":"/paper/2505.22126","citing_paper":"/paper/2507.01903"},"observation_digest":"sha256:0e16196efc23b7ae573c128de304e17212f5fe1256a079dfd37ff4609303ca0a","observation_id":"ceb77909-1200-4e3e-bf37-5ec36b4847c0","resolution":{"observed_at":"2026-08-06T20:45:12.217512Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2506.07642","last_updated":"2025-09-09T14:42:53Z","snapshot_observed_at":"2026-08-07T05:26:33.074954Z","submitted_at":"2025-06-09T11:07:55Z","title":"TreeReview: A Dynamic Tree of Questions Framework for Deep and Efficient LLM-based Scientific Peer Review","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2506.07642","snapshot_observed_at":"2026-08-06T20:45:12.221234Z","title":"Treereview: A dynamic tree of questions framework for deep and efficient llm-based scientific peer review","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2507.01903","last_updated":"2025-08-05T16:19:40Z","snapshot_observed_at":"2026-08-07T12:18:28.218519Z","submitted_at":"2025-07-02T17:19:20Z","title":"AI4Research: A Survey of Artificial Intelligence for Scientific Research","version":2},"reference_index":98,"source":"pdf_text","source_observed_at":"2026-08-06T20:45:12.221234Z"},"links":{"cited_paper":"/paper/2506.07642","citing_paper":"/paper/2507.01903"},"observation_digest":"sha256:bbdd18a8a9680763d6e7e8c2773916322640e7754c3327a63b58bec6da675fa8","observation_id":"da265e43-84a8-428a-beb0-6a34c072931a","resolution":{"observed_at":"2026-08-06T20:45:12.221234Z","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":"2026-08-06T20:45:12.224784Z","title":"Thetorontopapermatchingsystem: anautomatedpaper-reviewer assignment system","venue":null,"work_id":null,"year":2013},"citing_paper":{"arxiv_id":"2507.01903","last_updated":"2025-08-05T16:19:40Z","snapshot_observed_at":"2026-08-07T12:18:28.218519Z","submitted_at":"2025-07-02T17:19:20Z","title":"AI4Research: A Survey of Artificial Intelligence for Scientific Research","version":2},"reference_index":99,"source":"pdf_text","source_observed_at":"2026-08-06T20:45:12.224784Z"},"links":{"citing_paper":"/paper/2507.01903"},"observation_digest":"sha256:b7f224bf6def07fbed7495c697dac0fd319b3ad59c8101a5c4ee463c48910f5c","observation_id":"7172ed7c-4af7-4ea3-8a0a-fee9667acdb2","resolution":{"observed_at":"2026-08-06T20:45:12.224784Z","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":"2026-08-06T20:45:12.227761Z","title":"A framework for optimizing paper matching","venue":null,"work_id":null,"year":2011},"citing_paper":{"arxiv_id":"2507.01903","last_updated":"2025-08-05T16:19:40Z","snapshot_observed_at":"2026-08-07T12:18:28.218519Z","submitted_at":"2025-07-02T17:19:20Z","title":"AI4Research: A Survey of Artificial Intelligence for Scientific Research","version":2},"reference_index":100,"source":"pdf_text","source_observed_at":"2026-08-06T20:45:12.227761Z"},"links":{"citing_paper":"/paper/2507.01903"},"observation_digest":"sha256:1c00cff80e6e4944d254024e9a898847242ed1978d3bdc013dfa0db8848374d7","observation_id":"5aa52733-e761-4e94-b0a1-ab8e3cd7b6b5","resolution":{"observed_at":"2026-08-06T20:45:12.227761Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2507.01903","last_updated":"2025-08-05T16:19:40Z","latest_version":2,"primary_category":"cs.CL","snapshot_observed_at":"2026-08-07T12:18:28.218519Z","submitted_at":"2025-07-02T17:19:20Z","title":"AI4Research: A Survey of Artificial Intelligence for Scientific Research"},"reference_resolution":{"displayed":100,"state_counts":{"malformed_identifier":1,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":98,"verified_exact":1,"verified_fuzzy":0},"total_outbound_references":300},"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":"2026-08-07T06:34:17.273281+00:00","source":"crossref"},{"observed_at":"2026-08-07T06:34:11.927384+00:00","source":"retraction_watch"}],"thesis":"As of 7 August 2026, this Paper Citation Record lists 100 of 300 outbound references and 33 inbound Pith citation observations for arXiv:2507.01903."}