{"as_of":"2026-08-10T14:36:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:407f2ca1a3c91b01a89c791254007c0bc0e1090acb721e7e98a727b773b9a5d9","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":"2026-08-10T06:31:04.303077+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":"2026-08-08T04:30:09.801268Z","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":"2026-08-08T22:33:20.124926Z","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":"sha256:4fadf458d91d883744bb78a89722d854450c94470aea5a26440421a25f8361c5","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 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+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":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2507.01903","last_updated":"2025-08-05T16:19:40Z","snapshot_observed_at":"2026-08-08T04:30:09.801268Z","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":"2026-08-08T07:59:40.732848Z","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":"sha256:6f236fafbdb3dca0a194e17ac568d54d05f64bd82c924af5326e7de6054bb6f4","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":"2026-08-08T04:30:09.801268Z","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":"sha256:696f28df7151f559077b7189fa6a223569dbcaa44acc97b529713b51701ce28a","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 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+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":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2507.01903","last_updated":"2025-08-05T16:19:40Z","snapshot_observed_at":"2026-08-08T04:30:09.801268Z","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":"2026-08-10T00:17:40.727840Z","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:cd7f0e3011a24d0b736b2128316c4fc8d07dadbb7ba27a24054576bdb1b92f9b","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":"2026-08-08T04:30:09.801268Z","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":"sha256:4b050302092a526d45ca67a1d4b55669a6dff9e851e975cdf01da56bcf34abc9","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 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+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":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2507.01903","last_updated":"2025-08-05T16:19:40Z","snapshot_observed_at":"2026-08-08T04:30:09.801268Z","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:cc89aef24177c51757f7ce5b4274699fb7742b760fed8e7bf59a7e569c956eba","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":"2026-08-08T04:30:09.801268Z","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:fb81e2bf6296cefd213a134698b677b3f7212c90c90119587a2c14ec016c335a","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 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+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":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2507.01903","last_updated":"2025-08-05T16:19:40Z","snapshot_observed_at":"2026-08-08T04:30:09.801268Z","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":"2026-08-09T02:48:12.251795Z","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":"sha256:2c9555c9ba3ebca2ce6f46670dfab7bc9aa6cd43c0c89ae4a9ef972c0564d55d","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":"2026-08-08T04:30:09.801268Z","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:ec1b7989e4d983131e464201d43b5bc59605ea963705784090466275fc14c526","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 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+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":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2507.01903","last_updated":"2025-08-05T16:19:40Z","snapshot_observed_at":"2026-08-08T04:30:09.801268Z","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":"sha256:7871ddfaed07328628e9fca09e8fccb0c584200524a21c43c080539b9cece359","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 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+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":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2507.01903","last_updated":"2025-08-05T16:19:40Z","snapshot_observed_at":"2026-08-08T04:30:09.801268Z","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:aced49478018f06b2fc58236b9807ed2cb4e1bcb6384f9510afa8d4b4853b0ad","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 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+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":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2507.01903","last_updated":"2025-08-05T16:19:40Z","snapshot_observed_at":"2026-08-08T04:30:09.801268Z","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":"sha256:92a1ffe3161d3426d50d5671431b5aae8ae0ec8debb567dd6b750cbfd57148ed","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 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+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":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2507.01903","last_updated":"2025-08-05T16:19:40Z","snapshot_observed_at":"2026-08-08T04:30:09.801268Z","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:c03e2a807aed64654e0c23b93159b983990be06dd044e2faa5982dadb644f1d9","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 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+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":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2507.01903","last_updated":"2025-08-05T16:19:40Z","snapshot_observed_at":"2026-08-08T04:30:09.801268Z","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":"sha256:18d8c3ff04b0241e8c4f472662f6a8d058e927d8a097ac512e649d1e6690bcb6","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 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+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":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2507.01903","last_updated":"2025-08-05T16:19:40Z","snapshot_observed_at":"2026-08-08T04:30:09.801268Z","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":"sha256:098383891353b69bbd5d26cd497c9a3ed75e054365958348722fa86e4b20a73a","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 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+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":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2507.01903","last_updated":"2025-08-05T16:19:40Z","snapshot_observed_at":"2026-08-08T04:30:09.801268Z","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":"sha256:2d88baf7b62707750b85aaf2c8d93e7af9a680dc681340d7e32a246c4ce51c7d","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 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+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":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2507.01903","last_updated":"2025-08-05T16:19:40Z","snapshot_observed_at":"2026-08-08T04:30:09.801268Z","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:bc270cbdc51f74bfe23bdc41dde41719e3a07db6476b0a9c56e8d881c58cf569","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 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+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":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2507.01903","last_updated":"2025-08-05T16:19:40Z","snapshot_observed_at":"2026-08-08T04:30:09.801268Z","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":"sha256:379bcf91381e0cdc42061b0a1d01fc0b2e76966a4d314b7872f072a9dc30eb13","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 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+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":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2507.01903","last_updated":"2025-08-05T16:19:40Z","snapshot_observed_at":"2026-08-08T04:30:09.801268Z","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:f4c3c8add7230c795ab6049ea5e42db34e752b899dabc6d2f6abe9962c4d6b59","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 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+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":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2507.01903","last_updated":"2025-08-05T16:19:40Z","snapshot_observed_at":"2026-08-08T04:30:09.801268Z","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":"sha256:4d443861cd4708342a921cdf2322365d7a9c3fe573fa8376a8da050d769c56cb","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 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+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":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2507.01903","last_updated":"2025-08-05T16:19:40Z","snapshot_observed_at":"2026-08-08T04:30:09.801268Z","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":"sha256:64699c2277feda824518ab174498ad8437783bb5572bdf5f866dd4f19d01a7f5","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 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+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":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2507.01903","last_updated":"2025-08-05T16:19:40Z","snapshot_observed_at":"2026-08-08T04:30:09.801268Z","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:f2a003c732a54e48d8d5d3bedb52adb0bf394eacf0b80e11535f6f8009d15ad9","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 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+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":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2507.01903","last_updated":"2025-08-05T16:19:40Z","snapshot_observed_at":"2026-08-08T04:30:09.801268Z","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":"sha256:15d03d0769298c36da0e45cf63e6fe21a3baa8c9e9cc589d311ac2bcc817835c","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":"2026-08-08T04:30:09.801268Z","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:c9bce752be941e5ca5c668241f2a0bdb140e60d3fff99edcec1ea2e88ffae939","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 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+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":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2507.01903","last_updated":"2025-08-05T16:19:40Z","snapshot_observed_at":"2026-08-08T04:30:09.801268Z","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:a287b6e11578652a09bd0f4e6dfd208e2d36d73dc86847957da2edb59f9f27e2","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 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+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":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2507.01903","last_updated":"2025-08-05T16:19:40Z","snapshot_observed_at":"2026-08-08T04:30:09.801268Z","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":"2026-08-08T04:30:31.630171Z","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:ce37ac01947d8212e55fdce22cf12070d02e414bb7a1b2eb7f9e90eea8b0ab37","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":"2026-08-08T04:30:09.801268Z","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":"sha256:696e04cf029f232c53cd0a1105d75e3011396330ff8141f0ad7632cac665533c","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 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+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":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2507.01903","last_updated":"2025-08-05T16:19:40Z","snapshot_observed_at":"2026-08-08T04:30:09.801268Z","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:b1f24590627fce540a37daee7713fcda227e6b243aeeb0d87434c0f06b40ff21","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 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+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":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2507.01903","last_updated":"2025-08-05T16:19:40Z","snapshot_observed_at":"2026-08-08T04:30:09.801268Z","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":"2026-08-09T16:47:57.519950Z","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:b07008f2a47c38ecff4f376dde4072a091eb3c2fcdc89a3cad5daf579074c50f","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 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+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":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2507.01903","last_updated":"2025-08-05T16:19:40Z","snapshot_observed_at":"2026-08-08T04:30:09.801268Z","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:d0f588e9b656ea7b0821badd67ac1ee09c396f38008b5c0a37d58a2e10192572","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 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+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":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2507.01903","last_updated":"2025-08-05T16:19:40Z","snapshot_observed_at":"2026-08-08T04:30:09.801268Z","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:d76b2c94b531521bc320cbc2615ebc0ecdfbd9988687ed568b23fcb30451d49d","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 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+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":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2507.01903","last_updated":"2025-08-05T16:19:40Z","snapshot_observed_at":"2026-08-08T04:30:09.801268Z","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:bd66485627d34324d498534d5ee301a0011b0f505fb4196fb52f37a06437d741","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":"2026-08-08T04:30:09.801268Z","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":"sha256:43303295015f0c40f2c73128ded58e46f051e32ba75c48eb5c3abd82d9fdf076","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":"2026-08-08T04:30:09.801268Z","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":"sha256:092210aead6eb4b6e16501826115d0c235bc553bad968f595beb5c013d4f3b80","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":"2026-08-08T04:30:09.801268Z","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:be09471aeb642a6adca16bbc58eb2af64b4550cd9028fd43fd559ded147e80c4","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":"2026-08-08T04:30:09.801268Z","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:ee8882aa5a0eade0e0facbe0d46ab22656bb2910d07ebde0579ede3f139ba926","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":"2026-08-10T10:32:40.020913Z","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":"2026-08-08T04:30:09.801268Z","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":"sha256:3f5761fccf21614273656c7eea58bd34e08c2e8511134df449a6d9992f6f47ac","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":"2026-08-08T04:30:09.801268Z","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":"sha256:9f49422557be808df63a68306ce6ec4775610a8e5f40777a754b7452b7cb23aa","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":"2026-08-09T17:53:29.902227Z","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":"2026-08-08T04:30:09.801268Z","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":"sha256:628761ce7b24a473bab54b86b0bdbf1dd9382e2bb8d1da2317f5a29423ab19a1","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":"2026-08-08T03:04:39.404837Z","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":"2026-08-08T04:30:09.801268Z","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":"sha256:070615c7e67ea5f4f3cfc1f6e083fcb62daaab56253227b891184e92c5c5fbe0","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":"2026-08-10T00:06:23.775841Z","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":"2026-08-08T04:30:09.801268Z","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:a4be8a0300ca586a78ebbc8a79064c954231c17945286e4509f0b9225d26cd61","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":"2026-08-08T04:30:09.801268Z","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":"sha256:21b1d3ba5d969c879b84de50f8f90275e0c6cc445ebb1a391af05d12027fda70","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":"2026-08-08T04:30:09.801268Z","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":"sha256:894a836bbc8882bdba406f35ec5042976ac76a68be7e7c645615f4c41335cc31","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":"2026-08-08T04:30:09.801268Z","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":"sha256:86415d1b6690691ab93f86be1154fb2db817d868bde6917e8c2090fb2b0e7129","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":"2026-08-08T04:30:09.801268Z","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:c2ba149b78a96b2eff9d72fb5b2fa2b676ddef2c36a3a84c2238762c6ea0d8b1","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":"2026-08-08T04:30:09.801268Z","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:d3c3ae266f9aeb92cb71c973f3e120db66d1a91650b1b455e5d13143514878b2","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":"2026-08-08T04:30:09.801268Z","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":"sha256:0ee235ec2ce85a9557b255f81656f9ae8c83665429641f0f05fd2a126f464abd","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":"2026-08-08T04:30:09.801268Z","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":"sha256:83eaf195abe3bcb4ff317c77a17d043673b238e500159c0cf338567d2c4557a0","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":"2026-08-08T04:30:09.801268Z","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:fd470da597b357b70d8c17454383b76854192d32f1dc3476818ab3cdd838964e","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":"2026-08-08T04:30:09.801268Z","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:b0743e60a93d9be63f03818240b58eb1db52852abc645531044e227eb93c2cba","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":"2026-08-08T04:30:09.801268Z","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":"sha256:49a57387f1e98a7aae0bad39f1d68aca2805a155cb998f9335e3c2582a8738c7","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":"2026-08-08T04:30:09.801268Z","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":"sha256:3ec85dc2719078e9ffa5912b889f53dc34963e82d8fb962bb3da5aeab95d96c4","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":"2026-08-08T04:30:09.801268Z","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":"sha256:2e2bbcc67c9d18126f4981c81d8ab204c6ab9e56d0582b5ab557603b381ba068","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":"2026-08-08T04:30:09.801268Z","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":"sha256:6676fb78185ff4e26cca5c5dde0937ffc58fe430e12cb1788e72674b47f407da","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":"2026-08-08T04:30:09.801268Z","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:cd8aafe815cf721763ec9ebd69eaae894423f7b084d50767b20d8a6608b1e748","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":"2026-08-08T04:30:09.801268Z","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":"sha256:1b59aaac38a85eca8e3e87c4dce1095567c9796e23c27f8a6a8ef2f62127f0b7","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":"2026-08-08T04:30:09.801268Z","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":"sha256:4caa83bc84456e9d71de044ac92d475c8455708aa7e2625c78e840da2e6a18a2","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":"2026-08-08T04:30:09.801268Z","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":"sha256:071b2f9d8abc9fae2525040eb1a60519ce6261a20fe69da030445318f411064c","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":"2026-08-10T13:24:48.678844Z","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":"2026-08-08T04:30:09.801268Z","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":"sha256:4e3a8c737752cec20b1d096437c0670d114d0096015339b86f55177d4dd592bc","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":"2026-08-08T04:30:09.801268Z","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":"sha256:06032f176c7f52ec0479144b16cb5ad322287d47c1fa817d83c8d96bcb82e02d","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":"2026-08-08T04:30:09.801268Z","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:e12b03eca66c943f2d0e094cfba3051a460e322c09e9af2ca508b4a465fe06a7","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":"2026-08-08T04:30:09.801268Z","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":"sha256:86507584b300cfd681f5d2d688caa7aa5be4c0c0ecb316b56ca530e321c14e17","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":"2026-08-08T04:30:09.801268Z","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:b405008b0ce8bb65acf163df0a852ad3424a580828a871d1d638a6e93d374f7d","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":"2026-08-08T04:30:09.801268Z","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:ae35e5e0dc8bf52615d309c6ec08040463bcb8fb34969eaf41f4aeb89342af22","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":"2026-08-08T04:30:09.801268Z","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:db7981b6bc5e95f7cb49e192474f18a7cae49362aae50aadec0b174837a1e521","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":"2026-08-08T04:30:09.801268Z","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":"sha256:11bda4a80f7fdea90e8cddfcccb0684c38241180c553480c002a9d2b77c5cd82","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":"2026-08-08T04:30:09.801268Z","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:c6c136c029545302163d1228e98eb4c8a46cc1a93f2ec2f2a8d5102d205ff8b1","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":"2026-08-08T04:30:09.801268Z","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:c9b4bfa66a5c8c1f73d366b908552f4569b49127987cd30d2f18e8ce3af37705","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":"2026-08-10T02:36:27.870594Z","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":"2026-08-08T04:30:09.801268Z","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":"sha256:793eda75e4b9c3c4fd7bc12e61093b29ba90914ce9b181aa0203f36022b3bd0a","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":"2026-08-08T04:30:09.801268Z","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:fdbaf95f2440b19a10278a7b8acc227e543b6d94cb5a4e0f8a2b25e5fc41af40","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":"2026-08-08T04:30:09.801268Z","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":"sha256:8c34ef9ae75ec128be05290cc69ab6b351f3330161c7612e1df0274d20e4ed95","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":"2026-08-08T04:30:09.801268Z","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":"sha256:3adfa5dc6caef1e8223f6542e27b23905a245374f05e8dd5c0fdf4a0e6efc71f","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":"2026-08-08T04:30:09.801268Z","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:be8717f93571447a2108075a723f35cf913967996563a67ca862fb081b19f0a8","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":"2026-08-08T04:30:09.801268Z","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":"sha256:8d56283b1c6855697c183c1eb99fd1e6761cbca89ab84dced163255f87bd8ae7","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":"2026-08-08T04:30:09.801268Z","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":"sha256:113a8cedff513edbf5cc5392b6334560abebbca5aa372cfd026c607e678e2853","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":"2026-08-08T04:30:09.801268Z","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":"sha256:92454a1a67cd37e48ce16b6e682f6f8789cc7f9ba9cfea5ad40da5ff99fafd1f","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":"2026-08-08T04:30:09.801268Z","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:c8aba2bc2c4d6b138b1705bd92a944bcef7c044625f30fd12ac2b727777bac16","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":"2026-08-08T04:30:09.801268Z","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":"sha256:1d1bc5e54f51170f7f9499446017432d5f369c2fe32756a459c647521867da9d","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":"2026-08-08T04:30:09.801268Z","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":"sha256:444312fabae1f44922a4962ea8cd24650a60a591b5577397c64fa9570c6a8ba1","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":"2026-08-08T04:30:09.801268Z","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":"sha256:36d950977c9b60dcc9441ac1551947f08befec73ec1db7e8432c3f8f256e537d","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":"2026-08-08T04:30:09.801268Z","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":"sha256:427aefc5a9b315aac94d57b91d72b5c7e16a870bc7481a5a9e70b02d2f64369e","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":"2026-08-08T04:30:09.801268Z","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:cb052c6b12c4a97e8536eee3a893f5774ab496455805b1f99d1e759cf86043a0","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":"2026-08-08T04:30:09.801268Z","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:b5ae9c065bc61b78ab8476cd4cea1d31cb6315800f7e35c235e77b608f846c3b","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":"2026-08-08T04:30:09.801268Z","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:cc5db27de5ec8ed690da988324d4a906c4d66c6b18a9e27204a1c676a547f781","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":"2026-08-08T04:30:09.801268Z","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":"sha256:6122e1a9ebb6842a5551ab33b5754775510aa41b9d6d02c7c6ad94d26348da5a","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":"2026-08-08T04:30:09.801268Z","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":"sha256:8c1d1909cf319ee44206ddd5c835e06de0a1179ffe514b3aa474fa93c4da99a0","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":"2026-08-09T21:14:38.523705Z","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":"2026-08-08T04:30:09.801268Z","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:c2ec47dc4d5533a6e50916b191d57bc34b1bab8221a6207471de146465281535","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":"2026-08-08T23:00:04.073647Z","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":"2026-08-08T04:30:09.801268Z","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:aa23a81bf2f0a55852a236aac13ed9d1b7dc236b59aea720568fb4a71ed73cfe","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":"2026-08-08T04:30:09.801268Z","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":"sha256:63ac1657ad7b334de0309c7e97dc0c581cb33f72bb8905a157da904e427661c9","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":"2026-08-08T04:30:09.801268Z","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:f63721cb2ff21ab0afed3eaa23d9994e0ba0671f37b278c5baa32e39e5d229aa","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":"openalex","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-10T05:30:23.456663Z","title":"When automated assessment meets automated content generation: Examining text quality in the era of gpts.ACM Trans","venue":"ACM Transactions on Information Systems","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":"2026-08-08T04:30:09.801268Z","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":"sha256:46ca0a7a3221e00b490f8166dc01635ced3e7223798d5494a74cc35db0f6573e","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 2026-08-10T06:31:04.303077+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+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":"2026-08-08T04:30:09.801268Z","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":"sha256:89d61f41d3ad4d7c7f2853afc430632afbc032af1da93560e1a89d988221324c","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":"2026-08-08T04:30:09.801268Z","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":"sha256:37f5e1548a1b1ebf29827005df3ca1b4fa4ad260a0120d5027e57b8711b2c0e2","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":"2026-08-08T04:30:09.801268Z","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":"sha256:3fb9de111f2a6674cf4d0921e98001049fe15c62efe368d9420cd1f6ad380e6f","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":"2026-08-10T09:54:31.603110Z","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":"2026-08-08T04:30:09.801268Z","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":"sha256:20119e23b4c83fc0c92d57b96712eadca2ca28c6be141ff4472a6e3feda8f969","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":"2026-08-08T04:30:09.801268Z","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":"sha256:3d268bfdc4b691ba4153214c3b94807a13bd1f3d4da7e27935d76e1126bbeb9e","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":"2026-08-08T04:30:09.801268Z","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:b86c7e2f8954d9aa2b54c45414820a80e623fc291f25a85c7028199d189e6f68","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":"2026-08-08T04:30:09.801268Z","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:b4fa0fd5d3d955b9db4fbca17719b0dc25182cfbfaeacfad4846dadf870892a7","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":"2026-08-08T04:30:09.801268Z","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":"sha256:2adf42c15c70837b4b2c64398f2aa46d71813f6a3d1b29456b7f526dc6d4dc8e","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":"2026-08-08T04:30:09.801268Z","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:baf22eb4e74b4a8d427ca9f00df3c27409e14261ca97e8d7a93d6f02c4c403ff","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":"2026-08-08T04:30:09.801268Z","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":"sha256:782f390b791e5842ff7b9ea9167c1a06747543b786eb5375887206444c64c82e","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":"2026-08-08T04:30:09.801268Z","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":"sha256:25c09d239d7eb20edc4576d498d439a30e045e3492e5e1bfd08e796e1176e90f","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":"2026-08-08T04:30:09.801268Z","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":"sha256:82c4795725034f6d7da36a9472b69927cac33c0479586574cc173a911276fd9d","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":"2026-08-08T04:30:09.801268Z","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":"sha256:6f27da53ed247aecd4250d552777e7e29b84638885fc3344a0de349edcf5189c","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":"2026-08-08T04:30:09.801268Z","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":"sha256:4ca8dfe2cc6f5d0d157e733f2c7af0000387b77aa0628129089ace114f569b3d","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":"2026-08-08T04:30:09.801268Z","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:b414c3a5c8f1883b7e01dae51a785ed049b8d41820196e9b2cd4670cff1bae04","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":"2026-08-08T04:30:09.801268Z","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:b49d2e58524802e7a311e49b088b768639edfe1a77842e1ffef98a4936e6399f","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":"2026-08-08T04:30:09.801268Z","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:e86b5fb66438b2f7ed163935845ea44d107a697f624a851d341c0a66f26e23c7","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":"2026-08-08T04:30:09.801268Z","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:bc8a31c6b959bd83ea612b4979f792f6e5823b7ac635a407d88af82c01cdf37a","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":"2026-08-08T04:30:09.801268Z","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":"sha256:65408632cc2f327707d4387b2f8b1fe3064e96847f0f217af5591d16ae0c9a54","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":"2026-08-08T04:30:09.801268Z","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:ab9b3acd19c88ab71a930f05fb6461a3267e891264659b68bcbf33ac32af491e","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":"2026-08-08T04:30:09.801268Z","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":"sha256:27b5a7c4ad2221a8895b5bd4173f8cbb7f390601818ef7c9e7c1c7fd36a237f6","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":"2026-08-07T22:53:39.152523Z","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":"2026-08-08T04:30:09.801268Z","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:f8a38a07c76cc62f2623a09499d97c13915cb23c39d4c269d06cfb98eecc42b2","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":"2026-08-08T04:30:09.801268Z","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":"sha256:6876d85f462a13300833b919b89540e993bbd3fd68773f3fbc57c351e4a8a1f6","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":"2026-08-08T04:30:09.801268Z","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:c839baab8a7b82e0080d95e8024a2daaaebe649ce57ca1d10dce70219ca3b93b","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":"2026-08-08T04:30:09.801268Z","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":"sha256:5036ae79583613091059df2050bca486021921e9168824f1d90225e58f18ba5b","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":"2026-08-08T04:30:09.801268Z","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:e6ba262e926ee45a42ee6522d94272072da75d2730846598eb28a9df08fe8ec1","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":"2026-08-08T04:30:09.801268Z","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:a944100ebc2ae4ba924368de1d34002d9bfd1428fc567260785c3bafb037973f","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":"2026-08-08T04:30:09.801268Z","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":"sha256:5ea73a8dbbc6ab3c6fd6fe0fd0e83bec91b09f360620a0456d6f693536a8b327","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":"2026-08-08T04:30:09.801268Z","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:bb444f94921c3df8862edb016fcdf96e050c4d338fee5e93d6bb1a4b0c6f37ee","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":"2026-08-08T04:30:09.801268Z","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":"sha256:9edc02a71d421ffb8a98444353caeffddb5354fe6fd5649d74363a6d16ccd4d5","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":"2026-08-08T04:30:09.801268Z","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:a99537b6a74fd78945b497e94d0f30f1a4d719e2d48c0d93938cb13360dd2a14","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":"2026-08-08T04:30:09.801268Z","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:d4efe70e00fe65b2d9862787819eba85019d01de65d429915376d42fe95f8d2a","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":"2026-08-08T04:30:09.801268Z","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":"sha256:73c7c2a0ffe45bdd4e58c5e70fb6823fa72d11af718ca9c02f42c5e340c39d8b","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":"2026-08-08T04:30:09.801268Z","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":"sha256:8ae19cc958312a74a7008d2bd73fed549e1ec1a7b5c82e530f1f704ccbb6cd76","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":"2026-08-08T04:30:09.801268Z","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":"sha256:27eb609a884e01e25e3d055851214d1ad0aef9028c0acb38800b4cb2ba81de0e","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":"2026-08-08T04:30:09.801268Z","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":"sha256:043f24c8bc0138cef089f92b50e17247d72977e459ec0f7d2cb5e9ea68b89124","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":"2026-08-08T04:30:09.801268Z","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:f63541372d01c2e188143597f9f0951151fde94eae7283c6b0aa28b9391ee5b5","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":"2026-08-10T13:03:02.531646Z","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":"2026-08-08T04:30:09.801268Z","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":"sha256:61884883b2cd78630502dab8612ec84ed72cd9b3cd15a70dece27ef8078e1860","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":"2026-08-09T20:35:08.450172Z","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":"2026-08-08T04:30:09.801268Z","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:fcb9763c51b8bfb2d7dfca90f4c3d5580ceb7bd2a458a05cf17c8f6595f88cd1","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":"2026-08-09T20:34:30.520313Z","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":"2026-08-08T04:30:09.801268Z","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":"sha256:8ab29dd41379eb70c5add6b6e899b3af8841d61d2ad341664c523d7bd0f10408","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":"2026-08-08T04:30:09.801268Z","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":"sha256:2cf5155e2421ab6f22cbb4d45c5df180111e47e47afb4e66a4d51e17fd38f04d","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":"2026-08-08T04:30:09.801268Z","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":"sha256:0bcc3786932977492bfbb90d1e5d50442fed2753a9f4ddb7c9335c1779395ac9","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":"2026-08-08T04:30:09.801268Z","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":"2026-08-10T06:31:04.303077+00:00","source":"crossref"},{"observed_at":"2026-08-10T06:30:57.382061+00:00","source":"retraction_watch"}],"thesis":"As of 10 August 2026, this Paper Citation Record lists 100 of 300 outbound references and 33 inbound Pith citation observations for arXiv:2507.01903."}