{"as_of":"2026-08-09T07:16:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:0bd6fe1cfbed52d05fa048511d2ad3712a66fbd10c0aa9fc30fb0e885041fda7","coverage":[{"denominator":0,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":49,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":49,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-09T06:31:02.800959+00:00","state":"measured"},{"denominator":49,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":49,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-08T18:53:01.922089Z","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":13,"observed_at":"2026-08-05T02:28:24.338817Z","source":"arxiv_reference"}],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2404.07738","last_updated":"2025-02-09T08:15:44Z","snapshot_observed_at":"2026-07-06T17:58:52.016903Z","submitted_at":"2024-04-11T13:36:29Z","title":"ResearchAgent: Iterative Research Idea Generation over Scientific Literature with Large Language Models","version":2},"cited_work":{"arxiv_id":"2404.07738","doi":"10.48550/arxiv.2404.07738","metadata_source":"arxiv_reference","pith_arxiv_id":"2404.07738","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"K., Cucerzan, S","venue":"arXiv (Cornell University)","work_id":"41213a8f-51aa-4065-b3d5-2f154966db88","year":2021},"citing_paper":{"arxiv_id":"2408.06292","last_updated":"2024-09-01T00:41:18Z","snapshot_observed_at":"2026-07-06T18:59:43.564435Z","submitted_at":"2024-08-12T16:58:11Z","title":"The AI Scientist: Towards Fully Automated Open-Ended Scientific Discovery","version":3},"reference_index":6,"source":"arxiv_source","source_observed_at":"2026-05-11T04:42:31.555355Z"},"links":{"cited_paper":"/paper/2404.07738","citing_paper":"/paper/2408.06292"},"observation_digest":"sha256:3a53ef24167c5146d4bbe70aa74ca1e6ad06c65da3d45bebbb7ce79e5c7764f8","observation_id":"61bf799d-02ac-49e6-aacb-0d27d643dafe","resolution":{"observed_at":"2026-05-11T04:42:31.860963Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2404.07738","last_updated":"2025-02-09T08:15:44Z","snapshot_observed_at":"2026-07-06T17:58:52.016903Z","submitted_at":"2024-04-11T13:36:29Z","title":"ResearchAgent: Iterative Research Idea Generation over Scientific Literature with Large Language Models","version":2},"cited_work":{"arxiv_id":"2404.07738","doi":"10.48550/arxiv.2404.07738","metadata_source":"arxiv_reference","pith_arxiv_id":"2404.07738","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"K., Cucerzan, S","venue":"arXiv (Cornell University)","work_id":"41213a8f-51aa-4065-b3d5-2f154966db88","year":2021},"citing_paper":{"arxiv_id":"2409.14634","last_updated":"2026-05-16T16:23:07Z","snapshot_observed_at":"2026-07-06T19:19:37.350445Z","submitted_at":"2024-09-23T00:09:34Z","title":"Human-LLM Compound System for Scientific Ideation through Facet Recombination and Novelty Evaluation","version":7},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-05-23T20:58:01.255342Z"},"links":{"cited_paper":"/paper/2404.07738","citing_paper":"/paper/2409.14634"},"observation_digest":"sha256:7e15a939ede727b649c2d33a35cc1ba73d7aeaae52cceaf235e36e96c29c5ea8","observation_id":"df8dcb63-af6d-4877-9996-5d8ac98ffe19","resolution":{"observed_at":"2026-05-23T20:58:26.630346Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2404.07738","last_updated":"2025-02-09T08:15:44Z","snapshot_observed_at":"2026-07-06T17:58:52.016903Z","submitted_at":"2024-04-11T13:36:29Z","title":"ResearchAgent: Iterative Research Idea Generation over Scientific Literature with Large Language Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.07738","snapshot_observed_at":"2026-08-07T20:21:05.638112Z","title":"Baek, J., Jauhar, S","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2502.09858","last_updated":"2025-02-14T01:46:00Z","snapshot_observed_at":"2026-08-09T06:17:43.544912Z","submitted_at":"2025-02-14T01:46:00Z","title":"Automated Hypothesis Validation with Agentic Sequential Falsifications","version":1},"reference_index":2021,"source":"pdf_text","source_observed_at":"2026-08-07T20:21:05.638112Z"},"links":{"cited_paper":"/paper/2404.07738","citing_paper":"/paper/2502.09858"},"observation_digest":"sha256:e6724385cfa3e699cd5d6090a25179d44e97553577d1da86e75e1b9a4623b2b4","observation_id":"234c2a20-20f3-4497-b941-d37e8499f621","resolution":{"observed_at":"2026-08-07T20:21:05.638112Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2404.07738","last_updated":"2025-02-09T08:15:44Z","snapshot_observed_at":"2026-07-06T17:58:52.016903Z","submitted_at":"2024-04-11T13:36:29Z","title":"ResearchAgent: Iterative Research Idea Generation over Scientific Literature with Large Language Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.07738","snapshot_observed_at":"2026-08-07T19:10:00.281598Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2503.05712","last_updated":"2025-02-14T14:56:14Z","snapshot_observed_at":"2026-08-07T18:57:49.126462Z","submitted_at":"2025-02-14T14:56:14Z","title":"Automatic Evaluation Metrics for Artificially Generated Scientific Research","version":1},"reference_index":1,"source":"arxiv_source","source_observed_at":"2026-08-07T19:10:00.281598Z"},"links":{"cited_paper":"/paper/2404.07738","citing_paper":"/paper/2503.05712"},"observation_digest":"sha256:115098c2217814e9f2c518f849a95d726ad4f036d49b87eba2c96409c35119ec","observation_id":"7cab76ef-7b7a-4236-99f3-397249324150","resolution":{"observed_at":"2026-08-07T19:10:00.281598Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2404.07738","last_updated":"2025-02-09T08:15:44Z","snapshot_observed_at":"2026-07-06T17:58:52.016903Z","submitted_at":"2024-04-11T13:36:29Z","title":"ResearchAgent: Iterative Research Idea Generation over Scientific Literature with Large Language Models","version":2},"cited_work":{"arxiv_id":"2404.07738","doi":"10.48550/arxiv.2404.07738","metadata_source":"arxiv_reference","pith_arxiv_id":"2404.07738","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"K., Cucerzan, S","venue":"arXiv (Cornell University)","work_id":"41213a8f-51aa-4065-b3d5-2f154966db88","year":2021},"citing_paper":{"arxiv_id":"2504.13958","last_updated":"2025-04-16T21:45:32Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-04-16T21:45:32Z","title":"ToolRL: Reward is All Tool Learning Needs","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-05-14T00:26:48.291431Z"},"links":{"cited_paper":"/paper/2404.07738","citing_paper":"/paper/2504.13958"},"observation_digest":"sha256:3bb09bd02d1f2b0c6b93dc216a4d177a90d977cb005eaf0470c99708fa4f2b23","observation_id":"50cb9864-b874-4073-9774-74d88029539e","resolution":{"observed_at":"2026-05-14T00:26:48.335932Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2404.07738","last_updated":"2025-02-09T08:15:44Z","snapshot_observed_at":"2026-07-06T17:58:52.016903Z","submitted_at":"2024-04-11T13:36:29Z","title":"ResearchAgent: Iterative Research Idea Generation over Scientific Literature with Large Language Models","version":2},"cited_work":{"arxiv_id":"2404.07738","doi":"10.48550/arxiv.2404.07738","metadata_source":"arxiv_reference","pith_arxiv_id":"2404.07738","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"K., Cucerzan, S","venue":"arXiv (Cornell University)","work_id":"41213a8f-51aa-4065-b3d5-2f154966db88","year":2021},"citing_paper":{"arxiv_id":"2504.19678","last_updated":"2026-03-06T19:01:27Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-04-28T11:08:22Z","title":"From LLM Reasoning to Autonomous AI Agents: A Comprehensive Review","version":2},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-05-15T02:57:37.873567Z"},"links":{"cited_paper":"/paper/2404.07738","citing_paper":"/paper/2504.19678"},"observation_digest":"sha256:4fb4c29808f25abe39efbe985f535991a312d67d1f7dfb0cb440a7eb9a4837b2","observation_id":"721b20a7-e97a-4460-a71c-c51b2a0ca840","resolution":{"observed_at":"2026-05-15T02:57:38.035756Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2404.07738","last_updated":"2025-02-09T08:15:44Z","snapshot_observed_at":"2026-07-06T17:58:52.016903Z","submitted_at":"2024-04-11T13:36:29Z","title":"ResearchAgent: Iterative Research Idea Generation over Scientific Literature with Large Language Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.07738","snapshot_observed_at":"2026-08-07T15:42:42.956531Z","title":"Researchagent: Iterative research idea generation over scientific literature with large language models.CoRR, abs/2404.07738, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.14148","last_updated":"2025-05-20T09:55:31Z","snapshot_observed_at":"2026-08-07T15:37:17.307970Z","submitted_at":"2025-05-20T09:55:31Z","title":"MM-Agent: LLM as Agents for Real-world Mathematical Modeling Problem","version":1},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-08-07T15:42:42.956531Z"},"links":{"cited_paper":"/paper/2404.07738","citing_paper":"/paper/2505.14148"},"observation_digest":"sha256:57c6f0f21be7f9ae1006d6bbe177d70a9298992e5667aaee46bed9a8e420aedc","observation_id":"a180edb2-1235-41c7-bad1-22dc0014a1c4","resolution":{"observed_at":"2026-08-07T15:42:42.956531Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2404.07738","last_updated":"2025-02-09T08:15:44Z","snapshot_observed_at":"2026-07-06T17:58:52.016903Z","submitted_at":"2024-04-11T13:36:29Z","title":"ResearchAgent: Iterative Research Idea Generation over Scientific Literature with Large Language Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.07738","snapshot_observed_at":"2026-08-07T15:35:44.106103Z","title":"Researchagent: Iterative research idea generation over scientific literature with large language models","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.14599","last_updated":"2025-06-08T22:42:31Z","snapshot_observed_at":"2026-08-07T15:29:26.474390Z","submitted_at":"2025-05-20T16:49:40Z","title":"Toward Reliable Scientific Hypothesis Generation: Evaluating Truthfulness and Hallucination in Large Language Models","version":2},"reference_index":3,"source":"arxiv_source","source_observed_at":"2026-08-07T15:35:44.106103Z"},"links":{"cited_paper":"/paper/2404.07738","citing_paper":"/paper/2505.14599"},"observation_digest":"sha256:67abe4877d241dd1811fadb9c873c1e769d1292259cb102acad3ae4626d80669","observation_id":"d75a0f51-d44e-4073-9724-2b0c754c90ad","resolution":{"observed_at":"2026-08-07T15:35:44.106103Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2404.07738","last_updated":"2025-02-09T08:15:44Z","snapshot_observed_at":"2026-07-06T17:58:52.016903Z","submitted_at":"2024-04-11T13:36:29Z","title":"ResearchAgent: Iterative Research Idea Generation over Scientific Literature with Large Language Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.07738","snapshot_observed_at":"2026-08-07T14:31:17.207702Z","title":"Researchagent: Iterative research idea generation over scientific literature with large language models, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2505.18705","last_updated":"2025-05-24T13:54:38Z","snapshot_observed_at":"2026-08-07T14:25:00.518662Z","submitted_at":"2025-05-24T13:54:38Z","title":"AI-Researcher: Autonomous Scientific Innovation","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-07T14:31:17.207702Z"},"links":{"cited_paper":"/paper/2404.07738","citing_paper":"/paper/2505.18705"},"observation_digest":"sha256:02f4bdef6745e5b179553a357c691032e7c1b036f57f96f4f8ef2a3704e478b6","observation_id":"ed2a1464-e28c-4c9a-b4b8-2d9829a1ff77","resolution":{"observed_at":"2026-08-07T14:31:17.207702Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2404.07738","last_updated":"2025-02-09T08:15:44Z","snapshot_observed_at":"2026-07-06T17:58:52.016903Z","submitted_at":"2024-04-11T13:36:29Z","title":"ResearchAgent: Iterative Research Idea Generation over Scientific Literature with Large Language Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.07738","snapshot_observed_at":"2026-08-07T14:17:05.293825Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.19533","last_updated":"2025-05-26T05:39:57Z","snapshot_observed_at":"2026-08-08T00:00:45.680749Z","submitted_at":"2025-05-26T05:39:57Z","title":"ExAnte: A Benchmark for Ex-Ante Inference in Large Language Models","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-07T14:17:05.293825Z"},"links":{"cited_paper":"/paper/2404.07738","citing_paper":"/paper/2505.19533"},"observation_digest":"sha256:042e670510b26a11fdfff6606d5a27553e8a46a4cffb6e08ab80731bc5ecdfa0","observation_id":"4254cc86-41e6-45da-98e5-14cd09481235","resolution":{"observed_at":"2026-08-07T14:17:05.293825Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2404.07738","last_updated":"2025-02-09T08:15:44Z","snapshot_observed_at":"2026-07-06T17:58:52.016903Z","submitted_at":"2024-04-11T13:36:29Z","title":"ResearchAgent: Iterative Research Idea Generation over Scientific Literature with Large Language Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.07738","snapshot_observed_at":"2026-08-07T13:51:10.888133Z","title":"Researcha- gent: Iterative research idea generation 11 over scientific literature with large language models","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.21570","last_updated":"2025-05-27T06:42:41Z","snapshot_observed_at":"2026-08-07T13:44:51.341254Z","submitted_at":"2025-05-27T06:42:41Z","title":"Beyond Explainability: The Case for AI Validation","version":1},"reference_index":89,"source":"pdf_text","source_observed_at":"2026-08-07T13:51:10.888133Z"},"links":{"cited_paper":"/paper/2404.07738","citing_paper":"/paper/2505.21570"},"observation_digest":"sha256:8c36d3671b956b8ca0d238128172d081f40812616347fe89d0b1fd90da8f521c","observation_id":"37d5b821-9340-456f-9480-db4974cc6eed","resolution":{"observed_at":"2026-08-07T13:51:10.888133Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2404.07738","last_updated":"2025-02-09T08:15:44Z","snapshot_observed_at":"2026-07-06T17:58:52.016903Z","submitted_at":"2024-04-11T13:36:29Z","title":"ResearchAgent: Iterative Research Idea Generation over Scientific Literature with Large Language Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.07738","snapshot_observed_at":"2026-08-07T12:23:14.317930Z","title":"Pierre Azoulay, Joshua S Graff Zivin, and Gustavo Manso","venue":null,"work_id":null,"year":2011},"citing_paper":{"arxiv_id":"2505.24615","last_updated":"2025-05-30T14:08:13Z","snapshot_observed_at":"2026-08-07T12:14:58.000340Z","submitted_at":"2025-05-30T14:08:13Z","title":"Harnessing Large Language Models for Scientific Novelty Detection","version":1},"reference_index":2018,"source":"pdf_text","source_observed_at":"2026-08-07T12:23:14.317930Z"},"links":{"cited_paper":"/paper/2404.07738","citing_paper":"/paper/2505.24615"},"observation_digest":"sha256:5763783e64ad44b3eba937b4e965ff5e55f1474ecbe73033b9dc2159e3694ea3","observation_id":"be77ee47-e008-45df-add2-fe2216aece60","resolution":{"observed_at":"2026-08-07T12:23:14.317930Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2404.07738","last_updated":"2025-02-09T08:15:44Z","snapshot_observed_at":"2026-07-06T17:58:52.016903Z","submitted_at":"2024-04-11T13:36:29Z","title":"ResearchAgent: Iterative Research Idea Generation over Scientific Literature with Large Language Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.07738","snapshot_observed_at":"2026-08-07T12:20:41.572029Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2505.24785","last_updated":"2025-06-02T01:59:50Z","snapshot_observed_at":"2026-08-08T10:30:39.462765Z","submitted_at":"2025-05-30T16:46:29Z","title":"EXP-Bench: Can AI Conduct AI Research Experiments?","version":2},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-07T12:20:41.572029Z"},"links":{"cited_paper":"/paper/2404.07738","citing_paper":"/paper/2505.24785"},"observation_digest":"sha256:ee7bbbff47f2f8cc753883dc778205e0386afbf9916fdd8c543ed90b41dacae6","observation_id":"124fe480-644c-4eb9-8d69-516807eb4edf","resolution":{"observed_at":"2026-08-07T12:20:41.572029Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2404.07738","last_updated":"2025-02-09T08:15:44Z","snapshot_observed_at":"2026-07-06T17:58:52.016903Z","submitted_at":"2024-04-11T13:36:29Z","title":"ResearchAgent: Iterative Research Idea Generation over Scientific Literature with Large Language Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.07738","snapshot_observed_at":"2026-08-07T00:55:16.890485Z","title":null,"venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2506.12312","last_updated":"2025-06-14T02:22:28Z","snapshot_observed_at":"2026-08-09T04:53:53.558105Z","submitted_at":"2025-06-14T02:22:28Z","title":"Perspective on Utilizing Foundation Models for Laboratory Automation in Materials Research","version":1},"reference_index":61,"source":"pdf_text","source_observed_at":"2026-08-07T00:55:16.890485Z"},"links":{"cited_paper":"/paper/2404.07738","citing_paper":"/paper/2506.12312"},"observation_digest":"sha256:2517f83c464ad916bf34eec0a79d28d44f464341f6d0ca9ab90cc51d5c986314","observation_id":"5275622f-bca8-4169-8526-69c798093a88","resolution":{"observed_at":"2026-08-07T00:55:16.890485Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2404.07738","last_updated":"2025-02-09T08:15:44Z","snapshot_observed_at":"2026-07-06T17:58:52.016903Z","submitted_at":"2024-04-11T13:36:29Z","title":"ResearchAgent: Iterative Research Idea Generation over Scientific Literature with Large Language Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.07738","snapshot_observed_at":"2026-08-07T00:48:10.023073Z","title":null,"venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2506.12594","last_updated":"2025-06-14T18:19:05Z","snapshot_observed_at":"2026-08-07T11:53:13.790399Z","submitted_at":"2025-06-14T18:19:05Z","title":"A Comprehensive Survey of Deep Research: Systems, Methodologies, and Applications","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-07T00:48:10.023073Z"},"links":{"cited_paper":"/paper/2404.07738","citing_paper":"/paper/2506.12594"},"observation_digest":"sha256:9f21661078886d80aa24f1aca82351e325d2b5b96c666514af47c4ba0df26ffa","observation_id":"5745c445-5f30-4a4b-a437-a7bb397372eb","resolution":{"observed_at":"2026-08-07T00:48:10.023073Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2404.07738","last_updated":"2025-02-09T08:15:44Z","snapshot_observed_at":"2026-07-06T17:58:52.016903Z","submitted_at":"2024-04-11T13:36:29Z","title":"ResearchAgent: Iterative Research Idea Generation over Scientific Literature with Large Language Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.07738","snapshot_observed_at":"2026-08-06T23:48:43.916207Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.16010","last_updated":"2025-06-19T04:06:43Z","snapshot_observed_at":"2026-08-07T10:47:01.307481Z","submitted_at":"2025-06-19T04:06:43Z","title":"SimuPanel: A Novel Immersive Multi-Agent System to Simulate Interactive Expert Panel Discussion","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-08-06T23:48:43.916207Z"},"links":{"cited_paper":"/paper/2404.07738","citing_paper":"/paper/2506.16010"},"observation_digest":"sha256:c1917e287692034a785c8dcf8099f65da0d92a406c1315b7c493aa8b80dbfd7b","observation_id":"4d682cf3-43a6-4a94-ab50-6da3bf17e54a","resolution":{"observed_at":"2026-08-06T23:48:43.916207Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2404.07738","last_updated":"2025-02-09T08:15:44Z","snapshot_observed_at":"2026-07-06T17:58:52.016903Z","submitted_at":"2024-04-11T13:36:29Z","title":"ResearchAgent: Iterative Research Idea Generation over Scientific Literature with Large Language Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.07738","snapshot_observed_at":"2026-08-06T23:09:33.006277Z","title":"Researchagent: Iterative research idea generation over scientific literature with large language models","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.19613","last_updated":"2025-06-24T13:31:44Z","snapshot_observed_at":"2026-08-08T20:43:33.800853Z","submitted_at":"2025-06-24T13:31:44Z","title":"Position: Intelligent Science Laboratory Requires the Integration of Cognitive and Embodied AI","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-08-06T23:09:33.006277Z"},"links":{"cited_paper":"/paper/2404.07738","citing_paper":"/paper/2506.19613"},"observation_digest":"sha256:9405e10930db33465c162c523d8906f8edce25606aa7c291293108b44a9c5b67","observation_id":"d59e89cc-d46f-410a-a0d4-0ec56d940c89","resolution":{"observed_at":"2026-08-06T23:09:33.006277Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2404.07738","last_updated":"2025-02-09T08:15:44Z","snapshot_observed_at":"2026-07-06T17:58:52.016903Z","submitted_at":"2024-04-11T13:36:29Z","title":"ResearchAgent: Iterative Research Idea Generation over Scientific Literature with Large Language Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.07738","snapshot_observed_at":"2026-08-06T23:05:05.715235Z","title":"Researchagent: Iterative research idea generation over scientific literature with large language models, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.19998","last_updated":"2025-06-24T20:30:44Z","snapshot_observed_at":"2026-08-06T22:56:51.393502Z","submitted_at":"2025-06-24T20:30:44Z","title":"Doc2Agent: Scalable Generation of Tool-Using Agents from API Documentation","version":1},"reference_index":8,"source":"arxiv_source","source_observed_at":"2026-08-06T23:05:05.715235Z"},"links":{"cited_paper":"/paper/2404.07738","citing_paper":"/paper/2506.19998"},"observation_digest":"sha256:e94bc112b5fc69061eefcdb6daec818587c2f1d5ef8ac7e7274aad6e72bb25f7","observation_id":"0e7cf9e6-d0f7-44bc-9111-3a6598fe49de","resolution":{"observed_at":"2026-08-06T23:05:05.715235Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2404.07738","last_updated":"2025-02-09T08:15:44Z","snapshot_observed_at":"2026-07-06T17:58:52.016903Z","submitted_at":"2024-04-11T13:36:29Z","title":"ResearchAgent: Iterative Research Idea Generation over Scientific Literature with Large Language Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.07738","snapshot_observed_at":"2026-08-06T22:24:46.562225Z","title":"Researchagent: Iterative research idea generation over scientific literature with large language models","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2506.21763","last_updated":"2025-07-21T06:49:51Z","snapshot_observed_at":"2026-08-08T01:20:47.055827Z","submitted_at":"2025-06-26T20:44:51Z","title":"THE-Tree: Can Tracing Historical Evolution Enhance Scientific Verification and Reasoning?","version":2},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-06T22:24:46.562225Z"},"links":{"cited_paper":"/paper/2404.07738","citing_paper":"/paper/2506.21763"},"observation_digest":"sha256:47bf5aa3dec824ea876516b54e87c62bd5a1a290799488a019475a365272f8c7","observation_id":"7b2d3070-135e-486a-bcce-19211f19fcd7","resolution":{"observed_at":"2026-08-06T22:24:46.562225Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2404.07738","last_updated":"2025-02-09T08:15:44Z","snapshot_observed_at":"2026-07-06T17:58:52.016903Z","submitted_at":"2024-04-11T13:36:29Z","title":"ResearchAgent: Iterative Research Idea Generation over Scientific Literature with Large Language Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.07738","snapshot_observed_at":"2026-08-06T20:45:11.051532Z","title":"Researchagent: Itera- tive research idea generation over scientific literature with large language models.arXiv preprint arXiv:2404.07738, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.01903","last_updated":"2025-08-05T16:19:40Z","snapshot_observed_at":"2026-08-08T04:30:09.801268Z","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":"sha256:39e2069bb25cb229fc35a7e318551f63e1d22633ee5b7b5c5480a7ecce7e1c2d","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":{"arxiv_id":"2404.07738","last_updated":"2025-02-09T08:15:44Z","snapshot_observed_at":"2026-07-06T17:58:52.016903Z","submitted_at":"2024-04-11T13:36:29Z","title":"ResearchAgent: Iterative Research Idea Generation over Scientific Literature with Large Language Models","version":2},"cited_work":{"arxiv_id":"2404.07738","doi":"10.48550/arxiv.2404.07738","metadata_source":"arxiv_reference","pith_arxiv_id":"2404.07738","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"K., Cucerzan, S","venue":"arXiv (Cornell University)","work_id":"41213a8f-51aa-4065-b3d5-2f154966db88","year":2021},"citing_paper":{"arxiv_id":"2507.02212","last_updated":"2026-04-05T13:23:04Z","snapshot_observed_at":"2026-07-06T21:51:29.086752Z","submitted_at":"2025-07-03T00:21:38Z","title":"SciGA: A Comprehensive Dataset for Designing Graphical Abstracts in Academic Papers","version":2},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-05-19T05:59:59.221804Z"},"links":{"cited_paper":"/paper/2404.07738","citing_paper":"/paper/2507.02212"},"observation_digest":"sha256:f0c99d5b13d52f3ac93e8127f362d1a016345b95bafbaad9fc8f7088367ce3c1","observation_id":"f065aa9d-d9bc-4297-8afa-3ebef5b20e56","resolution":{"observed_at":"2026-05-19T06:02:07.416980Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2404.07738","last_updated":"2025-02-09T08:15:44Z","snapshot_observed_at":"2026-07-06T17:58:52.016903Z","submitted_at":"2024-04-11T13:36:29Z","title":"ResearchAgent: Iterative Research Idea Generation over Scientific Literature with Large Language Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.07738","snapshot_observed_at":"2026-08-06T19:28:14.975575Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.05528","last_updated":"2025-09-05T17:52:53Z","snapshot_observed_at":"2026-08-06T19:21:58.410006Z","submitted_at":"2025-07-07T22:56:37Z","title":"Conversational Education at Scale: A Multi-LLM Agent Workflow for Procedural Learning and Pedagogic Quality Assessment","version":2},"reference_index":2,"source":"arxiv_source","source_observed_at":"2026-08-06T19:28:14.975575Z"},"links":{"cited_paper":"/paper/2404.07738","citing_paper":"/paper/2507.05528"},"observation_digest":"sha256:0cd036f09c6ae86b86e9d045d24429d937dc5287b11afe993b1e136ff9f1c2f4","observation_id":"78a442b1-200c-40f0-b5e6-273acc94f8bd","resolution":{"observed_at":"2026-08-06T19:28:14.975575Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2404.07738","last_updated":"2025-02-09T08:15:44Z","snapshot_observed_at":"2026-07-06T17:58:52.016903Z","submitted_at":"2024-04-11T13:36:29Z","title":"ResearchAgent: Iterative Research Idea Generation over Scientific Literature with Large Language Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.07738","snapshot_observed_at":"2026-08-06T15:00:11.656746Z","title":null,"venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2507.17209","last_updated":"2025-07-23T05:02:54Z","snapshot_observed_at":"2026-08-09T02:14:12.817388Z","submitted_at":"2025-07-23T05:02:54Z","title":"HypoChainer: A Collaborative System Combining LLMs and Knowledge Graphs for Hypothesis-Driven Scientific Discovery","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-06T15:00:11.656746Z"},"links":{"cited_paper":"/paper/2404.07738","citing_paper":"/paper/2507.17209"},"observation_digest":"sha256:df357a0f3e6d6a4fc3cec5ce2fa056cd3ee6750e5fa094cf4e0a2f37d0488e82","observation_id":"d618aea7-1e01-425f-8d59-f9eeb3dccea3","resolution":{"observed_at":"2026-08-06T15:00:11.656746Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2404.07738","last_updated":"2025-02-09T08:15:44Z","snapshot_observed_at":"2026-07-06T17:58:52.016903Z","submitted_at":"2024-04-11T13:36:29Z","title":"ResearchAgent: Iterative Research Idea Generation over Scientific Literature with Large Language Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.07738","snapshot_observed_at":"2026-08-07T11:06:51.387619Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2507.19495","last_updated":"2025-06-04T02:12:17Z","snapshot_observed_at":"2026-08-08T15:06:14.621144Z","submitted_at":"2025-06-04T02:12:17Z","title":"Simulating Human Behavior with the Psychological-mechanism Agent: Integrating Feeling, Thought, and Action","version":1},"reference_index":2024,"source":"pdf_text","source_observed_at":"2026-08-07T11:06:51.387619Z"},"links":{"cited_paper":"/paper/2404.07738","citing_paper":"/paper/2507.19495"},"observation_digest":"sha256:38c3d7b895f3c4722e8454955733e857358e5ede33f232ce3100c5c506f15f14","observation_id":"affbaa9f-3733-41e3-9364-a431319e6622","resolution":{"observed_at":"2026-08-07T11:06:51.387619Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2404.07738","last_updated":"2025-02-09T08:15:44Z","snapshot_observed_at":"2026-07-06T17:58:52.016903Z","submitted_at":"2024-04-11T13:36:29Z","title":"ResearchAgent: Iterative Research Idea Generation over Scientific Literature with Large Language Models","version":2},"cited_work":{"arxiv_id":"2404.07738","doi":"10.48550/arxiv.2404.07738","metadata_source":"arxiv_reference","pith_arxiv_id":"2404.07738","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"K., Cucerzan, S","venue":"arXiv (Cornell University)","work_id":"41213a8f-51aa-4065-b3d5-2f154966db88","year":2021},"citing_paper":{"arxiv_id":"2507.21035","last_updated":"2026-05-17T21:43:43Z","snapshot_observed_at":"2026-07-06T22:04:01.721229Z","submitted_at":"2025-07-28T17:55:08Z","title":"GenoMAS: A Multi-Agent Framework for Scientific Discovery via Code-Driven Gene Expression Analysis","version":3},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-05-22T00:37:11.945418Z"},"links":{"cited_paper":"/paper/2404.07738","citing_paper":"/paper/2507.21035"},"observation_digest":"sha256:297b5d0de7684ae5edcf8ba670d0f9d88c7f3e870593208a41d142b80da9c85c","observation_id":"2a3ae6eb-3ffb-49a0-abb1-6bc8179b1afc","resolution":{"observed_at":"2026-05-22T00:40:51.123682Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2404.07738","last_updated":"2025-02-09T08:15:44Z","snapshot_observed_at":"2026-07-06T17:58:52.016903Z","submitted_at":"2024-04-11T13:36:29Z","title":"ResearchAgent: Iterative Research Idea Generation over Scientific Literature with Large Language Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.07738","snapshot_observed_at":"2026-08-05T15:32:37.373327Z","title":"ResearchAgent: Iterative Research Idea Generation over Scientific Literature with Large Language Models,","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2508.19800","last_updated":"2025-08-27T11:35:29Z","snapshot_observed_at":"2026-08-09T00:04:50.624732Z","submitted_at":"2025-08-27T11:35:29Z","title":"A Multi-Layered Framework for Modeling Human Biology: From Basic AI Agents to a Full-Body AI Agent","version":1},"reference_index":54,"source":"pdf_text","source_observed_at":"2026-08-05T15:32:37.373327Z"},"links":{"cited_paper":"/paper/2404.07738","citing_paper":"/paper/2508.19800"},"observation_digest":"sha256:0059bfe895a0533e3495a40ee7d44e7434941fd8ba5523e643e67a1b3550a995","observation_id":"df969006-830f-40ce-88bc-f5fd839b0764","resolution":{"observed_at":"2026-08-05T15:32:37.373327Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2404.07738","last_updated":"2025-02-09T08:15:44Z","snapshot_observed_at":"2026-07-06T17:58:52.016903Z","submitted_at":"2024-04-11T13:36:29Z","title":"ResearchAgent: Iterative Research Idea Generation over Scientific Literature with Large Language Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.07738","snapshot_observed_at":"2026-08-05T12:24:02.228568Z","title":"Researchagent: Iterative research idea generation over scientific literature with large language models","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.01684","last_updated":"2025-09-01T18:04:10Z","snapshot_observed_at":"2026-08-07T23:18:57.894257Z","submitted_at":"2025-09-01T18:04:10Z","title":"Reinforcement Learning for Machine Learning Engineering Agents","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-05T12:24:02.228568Z"},"links":{"cited_paper":"/paper/2404.07738","citing_paper":"/paper/2509.01684"},"observation_digest":"sha256:2129b641a0f4c552e298424b8ce2c63c8bca6059c3e568447ca84c6f4ef0cffc","observation_id":"594ff46b-6c87-4ac0-8d3a-9f4b2bdd3cc8","resolution":{"observed_at":"2026-08-05T12:24:02.228568Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2404.07738","last_updated":"2025-02-09T08:15:44Z","snapshot_observed_at":"2026-07-06T17:58:52.016903Z","submitted_at":"2024-04-11T13:36:29Z","title":"ResearchAgent: Iterative Research Idea Generation over Scientific Literature with Large Language Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.07738","snapshot_observed_at":"2026-08-05T11:01:14.023009Z","title":"Re- searchagent: Iterative research idea generation over scientific literature with large language models","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2509.03565","last_updated":"2025-09-03T15:45:03Z","snapshot_observed_at":"2026-08-08T13:23:45.396815Z","submitted_at":"2025-09-03T15:45:03Z","title":"ResearchPulse: Building Method-Experiment Chains through Multi-Document Scientific Inference","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-05T11:01:14.023009Z"},"links":{"cited_paper":"/paper/2404.07738","citing_paper":"/paper/2509.03565"},"observation_digest":"sha256:e8278999767dcf5ce4425acd816ed60c8cc74244781652aeecd30ad27389f20d","observation_id":"fa5d9654-af0d-41c0-9c94-d1f492252c6b","resolution":{"observed_at":"2026-08-05T11:01:14.023009Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2404.07738","last_updated":"2025-02-09T08:15:44Z","snapshot_observed_at":"2026-07-06T17:58:52.016903Z","submitted_at":"2024-04-11T13:36:29Z","title":"ResearchAgent: Iterative Research Idea Generation over Scientific Literature with Large Language Models","version":2},"cited_work":{"arxiv_id":"2404.07738","doi":"10.48550/arxiv.2404.07738","metadata_source":"arxiv_reference","pith_arxiv_id":"2404.07738","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"K., Cucerzan, S","venue":"arXiv (Cornell University)","work_id":"41213a8f-51aa-4065-b3d5-2f154966db88","year":2021},"citing_paper":{"arxiv_id":"2509.06503","last_updated":"2026-05-21T01:47:23Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-09-08T10:08:36Z","title":"An AI system to help scientists write expert-level empirical software","version":2},"reference_index":73,"source":"pdf_text","source_observed_at":"2026-05-21T22:43:38.306922Z"},"links":{"cited_paper":"/paper/2404.07738","citing_paper":"/paper/2509.06503"},"observation_digest":"sha256:1d34fa3f3939ba38a9b925d7c8e133d0f43e233e1f85482f694f3e8a992612fc","observation_id":"c1902214-e2c4-4992-9fe9-1c79e886582d","resolution":{"observed_at":"2026-05-21T22:44:24.297457Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2404.07738","last_updated":"2025-02-09T08:15:44Z","snapshot_observed_at":"2026-07-06T17:58:52.016903Z","submitted_at":"2024-04-11T13:36:29Z","title":"ResearchAgent: Iterative Research Idea Generation over Scientific Literature with Large Language Models","version":2},"cited_work":{"arxiv_id":"2404.07738","doi":"10.48550/arxiv.2404.07738","metadata_source":"arxiv_reference","pith_arxiv_id":"2404.07738","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"K., Cucerzan, S","venue":"arXiv (Cornell University)","work_id":"41213a8f-51aa-4065-b3d5-2f154966db88","year":2021},"citing_paper":{"arxiv_id":"2509.06503","last_updated":"2026-05-21T01:47:23Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-09-08T10:08:36Z","title":"An AI system to help scientists write expert-level empirical software","version":3},"reference_index":73,"source":"pdf_text","source_observed_at":"2026-05-22T13:21:45.164070Z"},"links":{"cited_paper":"/paper/2404.07738","citing_paper":"/paper/2509.06503"},"observation_digest":"sha256:a4cd0178fb00b55a1a44336ba9abca9db24c7921a6a2d09514126b6eaa137ce4","observation_id":"6a2599ef-ebed-4d9e-9cb3-51ae1c087985","resolution":{"observed_at":"2026-05-22T13:24:53.383135Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2404.07738","last_updated":"2025-02-09T08:15:44Z","snapshot_observed_at":"2026-07-06T17:58:52.016903Z","submitted_at":"2024-04-11T13:36:29Z","title":"ResearchAgent: Iterative Research Idea Generation over Scientific Literature with Large Language Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.07738","snapshot_observed_at":"2026-08-03T14:45:42.343939Z","title":"https://arxiv.org/ abs/2404.07738","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2512.19458","last_updated":"2026-07-07T09:00:18Z","snapshot_observed_at":"2026-08-06T03:19:31.860121Z","submitted_at":"2025-12-22T15:03:57Z","title":"VASP Agent: An Agentic Framework for Autonomous First-principles Calculations","version":2},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-08-03T14:45:42.343939Z"},"links":{"cited_paper":"/paper/2404.07738","citing_paper":"/paper/2512.19458"},"observation_digest":"sha256:5482fbf9873dffa65c27ffe7bd755ed60a8816eb988900043ba87fce83d3b720","observation_id":"f15bfbd2-e355-4e62-bcc7-ca9e7019fc85","resolution":{"observed_at":"2026-08-03T14:45:42.343939Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2404.07738","last_updated":"2025-02-09T08:15:44Z","snapshot_observed_at":"2026-07-06T17:58:52.016903Z","submitted_at":"2024-04-11T13:36:29Z","title":"ResearchAgent: Iterative Research Idea Generation over Scientific Literature with Large Language Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.07738","snapshot_observed_at":"2026-08-03T05:17:18.379513Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2602.02905","last_updated":"2026-07-10T18:07:40Z","snapshot_observed_at":"2026-08-09T05:22:17.614080Z","submitted_at":"2026-02-02T23:21:13Z","title":"FIRE-Bench: Evaluating AI Agents on the Rediscovery of Scientific Insights","version":2},"reference_index":2025,"source":"pdf_text","source_observed_at":"2026-08-03T05:17:18.379513Z"},"links":{"cited_paper":"/paper/2404.07738","citing_paper":"/paper/2602.02905"},"observation_digest":"sha256:831eda1ad238d8ba03d19bb6dffddac401e71d0117a803c7c79e2d8ce7e738a4","observation_id":"da817f0d-259e-41ab-a4eb-2561511ca1a3","resolution":{"observed_at":"2026-08-03T05:17:18.379513Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2404.07738","last_updated":"2025-02-09T08:15:44Z","snapshot_observed_at":"2026-07-06T17:58:52.016903Z","submitted_at":"2024-04-11T13:36:29Z","title":"ResearchAgent: Iterative Research Idea Generation over Scientific Literature with Large Language Models","version":2},"cited_work":{"arxiv_id":"2404.07738","doi":"10.48550/arxiv.2404.07738","metadata_source":"arxiv_reference","pith_arxiv_id":"2404.07738","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"K., Cucerzan, S","venue":"arXiv (Cornell University)","work_id":"41213a8f-51aa-4065-b3d5-2f154966db88","year":2021},"citing_paper":{"arxiv_id":"2604.05587","last_updated":"2026-04-07T08:29:41Z","snapshot_observed_at":"2026-07-06T22:54:16.913706Z","submitted_at":"2026-04-07T08:29:41Z","title":"ResearchEVO: An End-to-End Framework for Automated Scientific Discovery and Documentation","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-05-10T19:45:04.315752Z"},"links":{"cited_paper":"/paper/2404.07738","citing_paper":"/paper/2604.05587"},"observation_digest":"sha256:8c7f309b0e59a97ceb44a7ed19a97a0fd145929de517a1e76c2212497645e1c6","observation_id":"92dedf71-cb38-401c-8a21-6b5eb938ded0","resolution":{"observed_at":"2026-05-10T22:30:53.729163Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2404.07738","last_updated":"2025-02-09T08:15:44Z","snapshot_observed_at":"2026-07-06T17:58:52.016903Z","submitted_at":"2024-04-11T13:36:29Z","title":"ResearchAgent: Iterative Research Idea Generation over Scientific Literature with Large Language Models","version":2},"cited_work":{"arxiv_id":"2404.07738","doi":"10.48550/arxiv.2404.07738","metadata_source":"arxiv_reference","pith_arxiv_id":"2404.07738","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"K., Cucerzan, S","venue":"arXiv (Cornell University)","work_id":"41213a8f-51aa-4065-b3d5-2f154966db88","year":2021},"citing_paper":{"arxiv_id":"2604.05854","last_updated":"2026-04-07T13:16:31Z","snapshot_observed_at":"2026-08-02T12:14:23.144370Z","submitted_at":"2026-04-07T13:16:31Z","title":"Deep Researcher Agent: An Autonomous Framework for 24/7 Deep Learning Experimentation with Zero-Cost Monitoring","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-05-10T18:37:23.176476Z"},"links":{"cited_paper":"/paper/2404.07738","citing_paper":"/paper/2604.05854"},"observation_digest":"sha256:4bee721e3a86ee0041b055f55d5e5e533d9aaaeb88481751c4838c2ec5f0020e","observation_id":"56392007-ea5a-44c6-a940-fc1c51bd55d1","resolution":{"observed_at":"2026-05-11T00:15:54.454844Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2404.07738","last_updated":"2025-02-09T08:15:44Z","snapshot_observed_at":"2026-07-06T17:58:52.016903Z","submitted_at":"2024-04-11T13:36:29Z","title":"ResearchAgent: Iterative Research Idea Generation over Scientific Literature with Large Language Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.07738","snapshot_observed_at":"2026-07-12T21:55:01.804645Z","title":"https://doi.org/10.48550/arXiv.2404.07738 arXiv:2404.07738 [cs]","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2604.11537","last_updated":"2026-06-18T19:20:41Z","snapshot_observed_at":"2026-07-12T21:55:00.535568Z","submitted_at":"2026-04-13T14:32:56Z","title":"Beyond the Golden Record: Toward a Design Theory for Trustworthy Master Data Management with Self-Sovereign Identity","version":3},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-07-12T21:55:01.804645Z"},"links":{"cited_paper":"/paper/2404.07738","citing_paper":"/paper/2604.11537"},"observation_digest":"sha256:4b431b6767db155f9ce1544c9069f1e2de6ce1f3cc5db1beba45d49c2e61bbc7","observation_id":"fea53f48-a124-418d-a5ef-8ec419932ba8","resolution":{"observed_at":"2026-07-12T21:55:01.804645Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2404.07738","last_updated":"2025-02-09T08:15:44Z","snapshot_observed_at":"2026-07-06T17:58:52.016903Z","submitted_at":"2024-04-11T13:36:29Z","title":"ResearchAgent: Iterative Research Idea Generation over Scientific Literature with Large Language Models","version":2},"cited_work":{"arxiv_id":"2404.07738","doi":"10.48550/arxiv.2404.07738","metadata_source":"arxiv_reference","pith_arxiv_id":"2404.07738","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"K., Cucerzan, S","venue":"arXiv (Cornell University)","work_id":"41213a8f-51aa-4065-b3d5-2f154966db88","year":2021},"citing_paper":{"arxiv_id":"2604.11538","last_updated":"2026-04-13T14:32:57Z","snapshot_observed_at":"2026-08-04T00:54:41.979170Z","submitted_at":"2026-04-13T14:32:57Z","title":"ResearchCube: Multi-Dimensional Trade-off Exploration for Research Ideation","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-05-10T15:55:52.452061Z"},"links":{"cited_paper":"/paper/2404.07738","citing_paper":"/paper/2604.11538"},"observation_digest":"sha256:9faf2b9c6e9174d552e24fb6c2d90e0ffbb6f8046a25385e1d3b56ab8a51f591","observation_id":"793bca19-caba-410e-ab61-e28ec201a52b","resolution":{"observed_at":"2026-05-10T21:40:47.929205Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2404.07738","last_updated":"2025-02-09T08:15:44Z","snapshot_observed_at":"2026-07-06T17:58:52.016903Z","submitted_at":"2024-04-11T13:36:29Z","title":"ResearchAgent: Iterative Research Idea Generation over Scientific Literature with Large Language Models","version":2},"cited_work":{"arxiv_id":"2404.07738","doi":"10.48550/arxiv.2404.07738","metadata_source":"arxiv_reference","pith_arxiv_id":"2404.07738","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"K., Cucerzan, S","venue":"arXiv (Cornell University)","work_id":"41213a8f-51aa-4065-b3d5-2f154966db88","year":2021},"citing_paper":{"arxiv_id":"2604.12144","last_updated":"2026-07-01T22:34:57Z","snapshot_observed_at":"2026-08-02T05:18:11.450897Z","submitted_at":"2026-04-13T23:48:35Z","title":"VERITAS: A Multi-Agent Co-Scientist for Verifiable Image-Derived Hypothesis Testing","version":1},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-05-10T14:56:06.372343Z"},"links":{"cited_paper":"/paper/2404.07738","citing_paper":"/paper/2604.12144"},"observation_digest":"sha256:27aa238468d0bc752bd60abcdc8a3a76b596a275db9c1b74eb5a22d66f69707a","observation_id":"56adca3e-6062-4b70-a1be-fc4a7100565e","resolution":{"observed_at":"2026-05-11T11:26:02.190144Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2404.07738","last_updated":"2025-02-09T08:15:44Z","snapshot_observed_at":"2026-07-06T17:58:52.016903Z","submitted_at":"2024-04-11T13:36:29Z","title":"ResearchAgent: Iterative Research Idea Generation over Scientific Literature with Large Language Models","version":2},"cited_work":{"arxiv_id":"2404.07738","doi":"10.48550/arxiv.2404.07738","metadata_source":"arxiv_reference","pith_arxiv_id":"2404.07738","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"K., Cucerzan, S","venue":"arXiv (Cornell University)","work_id":"41213a8f-51aa-4065-b3d5-2f154966db88","year":2021},"citing_paper":{"arxiv_id":"2605.11258","last_updated":"2026-05-11T21:35:44Z","snapshot_observed_at":"2026-08-07T17:33:40.465485Z","submitted_at":"2026-05-11T21:35:44Z","title":"Unlocking LLM Creativity in Science through Analogical Reasoning","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-05-13T01:53:26.159310Z"},"links":{"cited_paper":"/paper/2404.07738","citing_paper":"/paper/2605.11258"},"observation_digest":"sha256:6f2836ee66dbbec9f84f56d098100f7e8536d41495cb73579d5d5757bb0a7221","observation_id":"b08ca8d5-c4b3-4fb5-91f3-8823d5c3e4dd","resolution":{"observed_at":"2026-05-13T01:57:05.733688Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2404.07738","last_updated":"2025-02-09T08:15:44Z","snapshot_observed_at":"2026-07-06T17:58:52.016903Z","submitted_at":"2024-04-11T13:36:29Z","title":"ResearchAgent: Iterative Research Idea Generation over Scientific Literature with Large Language Models","version":2},"cited_work":{"arxiv_id":"2404.07738","doi":"10.48550/arxiv.2404.07738","metadata_source":"arxiv_reference","pith_arxiv_id":"2404.07738","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"K., Cucerzan, S","venue":"arXiv (Cornell University)","work_id":"41213a8f-51aa-4065-b3d5-2f154966db88","year":2021},"citing_paper":{"arxiv_id":"2605.11532","last_updated":"2026-05-12T04:58:08Z","snapshot_observed_at":"2026-07-06T23:23:21.034839Z","submitted_at":"2026-05-12T04:58:08Z","title":"Read, Grep, and Synthesize: Diagnosing Cross-Domain Seed Exposure for LLM Research Ideation","version":1},"reference_index":9,"source":"arxiv_source","source_observed_at":"2026-05-13T01:06:02.275470Z"},"links":{"cited_paper":"/paper/2404.07738","citing_paper":"/paper/2605.11532"},"observation_digest":"sha256:251def4f559899655c402107ef2fa3de3eb69a6b0827ce5f9711754619281745","observation_id":"d072b259-4911-49c5-a67f-d481d00c4e49","resolution":{"observed_at":"2026-05-13T01:07:00.067830Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2404.07738","last_updated":"2025-02-09T08:15:44Z","snapshot_observed_at":"2026-07-06T17:58:52.016903Z","submitted_at":"2024-04-11T13:36:29Z","title":"ResearchAgent: Iterative Research Idea Generation over Scientific Literature with Large Language Models","version":2},"cited_work":{"arxiv_id":"2404.07738","doi":"10.48550/arxiv.2404.07738","metadata_source":"arxiv_reference","pith_arxiv_id":"2404.07738","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"K., Cucerzan, S","venue":"arXiv (Cornell University)","work_id":"41213a8f-51aa-4065-b3d5-2f154966db88","year":2021},"citing_paper":{"arxiv_id":"2605.14790","last_updated":"2026-05-14T12:57:56Z","snapshot_observed_at":"2026-07-06T23:26:09.066863Z","submitted_at":"2026-05-14T12:57:56Z","title":"Graphs of Research: Citation Evolution Graphs as Supervision for Research Idea Generation","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-06-30T20:52:32.567107Z"},"links":{"cited_paper":"/paper/2404.07738","citing_paper":"/paper/2605.14790"},"observation_digest":"sha256:90e672de96c41865b54b3f5301a18beb886cc81ed0038d2a7fd2a91afa78faa9","observation_id":"64f0a39f-23a2-4e1f-94ab-25fcc6c113e3","resolution":{"observed_at":"2026-06-30T20:55:04.099681Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2404.07738","last_updated":"2025-02-09T08:15:44Z","snapshot_observed_at":"2026-07-06T17:58:52.016903Z","submitted_at":"2024-04-11T13:36:29Z","title":"ResearchAgent: Iterative Research Idea Generation over Scientific Literature with Large Language Models","version":2},"cited_work":{"arxiv_id":"2404.07738","doi":"10.48550/arxiv.2404.07738","metadata_source":"arxiv_reference","pith_arxiv_id":"2404.07738","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"K., Cucerzan, S","venue":"arXiv (Cornell University)","work_id":"41213a8f-51aa-4065-b3d5-2f154966db88","year":2021},"citing_paper":{"arxiv_id":"2606.17628","last_updated":"2026-06-16T07:33:53Z","snapshot_observed_at":"2026-08-05T17:08:33.405254Z","submitted_at":"2026-06-16T07:33:53Z","title":"OPD-Evolver: Cultivating Holistic Agent Evolver via On-Policy Distillation","version":1},"reference_index":105,"source":"arxiv_source","source_observed_at":"2026-06-27T01:07:49.603969Z"},"links":{"cited_paper":"/paper/2404.07738","citing_paper":"/paper/2606.17628"},"observation_digest":"sha256:5657ca6e2c2ed8ce2d508afd0a1e98944102b289b4ffa9bfd50402f913d1c9bf","observation_id":"7165ffa8-660a-44a0-868d-05a9f31e3a48","resolution":{"observed_at":"2026-07-03T20:48:56.350559Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2404.07738","last_updated":"2025-02-09T08:15:44Z","snapshot_observed_at":"2026-07-06T17:58:52.016903Z","submitted_at":"2024-04-11T13:36:29Z","title":"ResearchAgent: Iterative Research Idea Generation over Scientific Literature with Large Language Models","version":2},"cited_work":{"arxiv_id":"2404.07738","doi":"10.48550/arxiv.2404.07738","metadata_source":"arxiv_reference","pith_arxiv_id":"2404.07738","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"K., Cucerzan, S","venue":"arXiv (Cornell University)","work_id":"41213a8f-51aa-4065-b3d5-2f154966db88","year":2021},"citing_paper":{"arxiv_id":"2606.22610","last_updated":"2026-06-21T17:37:01Z","snapshot_observed_at":"2026-07-06T23:57:28.172988Z","submitted_at":"2026-06-21T17:37:01Z","title":"PaperClaw: Harnessing Agents for Autonomous Research and Human-in-the-Loop Refinement","version":1},"reference_index":59,"source":"arxiv_source","source_observed_at":"2026-06-26T10:36:14.840581Z"},"links":{"cited_paper":"/paper/2404.07738","citing_paper":"/paper/2606.22610"},"observation_digest":"sha256:db0b0bfd439cd0edbffad2ff8dc4e9aede0f4209caaaa48a91fe9146fcfb23e9","observation_id":"73b81e38-5610-4f13-8cb7-5d46aa541d4b","resolution":{"observed_at":"2026-07-04T08:59:43.451462Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2404.07738","last_updated":"2025-02-09T08:15:44Z","snapshot_observed_at":"2026-07-06T17:58:52.016903Z","submitted_at":"2024-04-11T13:36:29Z","title":"ResearchAgent: Iterative Research Idea Generation over Scientific Literature with Large Language Models","version":2},"cited_work":{"arxiv_id":"2404.07738","doi":"10.48550/arxiv.2404.07738","metadata_source":"arxiv_reference","pith_arxiv_id":"2404.07738","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"K., Cucerzan, S","venue":"arXiv (Cornell University)","work_id":"41213a8f-51aa-4065-b3d5-2f154966db88","year":2021},"citing_paper":{"arxiv_id":"2606.30775","last_updated":"2026-06-29T18:06:43Z","snapshot_observed_at":"2026-07-07T00:04:34.491408Z","submitted_at":"2026-06-29T18:06:43Z","title":"A Single Rewrite Suffices: Empirical Lessons from Production Skill Description Optimization","version":1},"reference_index":100,"source":"arxiv_source","source_observed_at":"2026-07-01T02:32:19.425550Z"},"links":{"cited_paper":"/paper/2404.07738","citing_paper":"/paper/2606.30775"},"observation_digest":"sha256:196f543aae2c3d90a82eb7f1ffc9fd4e6377d3b3d8c49e38616c034100027a08","observation_id":"bd03dd2d-22dc-4960-bacb-61472b354122","resolution":{"observed_at":"2026-07-01T12:05:43.621686Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2404.07738","last_updated":"2025-02-09T08:15:44Z","snapshot_observed_at":"2026-07-06T17:58:52.016903Z","submitted_at":"2024-04-11T13:36:29Z","title":"ResearchAgent: Iterative Research Idea Generation over Scientific Literature with Large Language Models","version":2},"cited_work":{"arxiv_id":"2404.07738","doi":"10.48550/arxiv.2404.07738","metadata_source":"arxiv_reference","pith_arxiv_id":"2404.07738","snapshot_observed_at":"2026-08-05T02:28:24.338817Z","title":"K., Cucerzan, S","venue":"arXiv (Cornell University)","work_id":"41213a8f-51aa-4065-b3d5-2f154966db88","year":2021},"citing_paper":{"arxiv_id":"2606.31651","last_updated":"2026-07-13T07:29:01Z","snapshot_observed_at":"2026-07-16T23:18:46.390607Z","submitted_at":"2026-06-30T13:30:24Z","title":"FARS: A Fully Automated Research System Deployed at Scale","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-07-01T05:18:53.840963Z"},"links":{"cited_paper":"/paper/2404.07738","citing_paper":"/paper/2606.31651"},"observation_digest":"sha256:9962e126d668646fa99dcf609369ea12fe8170253b834af392e31b5671277f11","observation_id":"f2ddd763-e945-4d72-a793-e53779674a0b","resolution":{"observed_at":"2026-07-01T10:35:42.690381Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2404.07738","last_updated":"2025-02-09T08:15:44Z","snapshot_observed_at":"2026-07-06T17:58:52.016903Z","submitted_at":"2024-04-11T13:36:29Z","title":"ResearchAgent: Iterative Research Idea Generation over Scientific Literature with Large Language Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.07738","snapshot_observed_at":"2026-07-14T16:55:37.417202Z","title":"Alina Beygelzimer, Yann N","venue":null,"work_id":null,"year":2021},"citing_paper":{"arxiv_id":"2606.31651","last_updated":"2026-07-13T07:29:01Z","snapshot_observed_at":"2026-07-16T23:18:46.390607Z","submitted_at":"2026-06-30T13:30:24Z","title":"FARS: A Fully Automated Research System Deployed at Scale","version":2},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-07-14T16:55:37.417202Z"},"links":{"cited_paper":"/paper/2404.07738","citing_paper":"/paper/2606.31651"},"observation_digest":"sha256:a9f317f46e54acd0911cd374e9fe28484754254d5d7503113e06a6b3772b125b","observation_id":"9ca7e5c5-d84a-45aa-af53-45729841a9b1","resolution":{"observed_at":"2026-07-14T16:55:37.417202Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2404.07738","last_updated":"2025-02-09T08:15:44Z","snapshot_observed_at":"2026-07-06T17:58:52.016903Z","submitted_at":"2024-04-11T13:36:29Z","title":"ResearchAgent: Iterative Research Idea Generation over Scientific Literature with Large Language Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.07738","snapshot_observed_at":"2026-07-14T13:58:30.439198Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.10144","last_updated":"2026-07-20T11:28:47Z","snapshot_observed_at":"2026-08-03T09:33:29.395789Z","submitted_at":"2026-07-11T06:04:29Z","title":"IdeaTrail: Full-Process Agent Trajectories for Scientific Ideation","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-07-14T13:58:30.439198Z"},"links":{"cited_paper":"/paper/2404.07738","citing_paper":"/paper/2607.10144"},"observation_digest":"sha256:a53faeac798ff39713adbcf4ec2dc9c17c8458463413d22c0e7a27c276b414e1","observation_id":"4ec76f53-8070-49b2-9c1c-681351284ed2","resolution":{"observed_at":"2026-07-14T13:58:30.439198Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2404.07738","last_updated":"2025-02-09T08:15:44Z","snapshot_observed_at":"2026-07-06T17:58:52.016903Z","submitted_at":"2024-04-11T13:36:29Z","title":"ResearchAgent: Iterative Research Idea Generation over Scientific Literature with Large Language Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.07738","snapshot_observed_at":"2026-08-02T07:23:15.421119Z","title":null,"venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.10144","last_updated":"2026-07-20T11:28:47Z","snapshot_observed_at":"2026-08-03T09:33:29.395789Z","submitted_at":"2026-07-11T06:04:29Z","title":"IdeaTrail: Full-Process Agent Trajectories for Scientific Ideation","version":3},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-08-02T07:23:15.421119Z"},"links":{"cited_paper":"/paper/2404.07738","citing_paper":"/paper/2607.10144"},"observation_digest":"sha256:fdd03b0768fefa94e778823a6a4e31d33de8ccf4f1def6f26c8437453ceb8c67","observation_id":"403ca123-ccf3-49f8-8f62-1b13618deeab","resolution":{"observed_at":"2026-08-02T07:23:15.421119Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2404.07738","last_updated":"2025-02-09T08:15:44Z","snapshot_observed_at":"2026-07-06T17:58:52.016903Z","submitted_at":"2024-04-11T13:36:29Z","title":"ResearchAgent: Iterative Research Idea Generation over Scientific Literature with Large Language Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.07738","snapshot_observed_at":"2026-08-08T18:53:01.922089Z","title":"arXiv preprint arXiv:2404.07738 , year =","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.04374","last_updated":"2026-08-05T02:31:48Z","snapshot_observed_at":"2026-08-08T23:11:33.094896Z","submitted_at":"2026-08-05T02:31:48Z","title":"FinReportBench: Measuring and Improving Institution-Grade Financial Report Generation","version":1},"reference_index":19,"source":"arxiv_source","source_observed_at":"2026-08-08T18:53:01.922089Z"},"links":{"cited_paper":"/paper/2404.07738","citing_paper":"/paper/2608.04374"},"observation_digest":"sha256:b62479b9f2b47a3eca98ee4a3bf860601b53d659afa0ee171065a2830611d181","observation_id":"bdff11d1-5f53-47a4-92d1-79a379f442d0","resolution":{"observed_at":"2026-08-08T18:53:01.922089Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2404.07738","last_updated":"2025-02-09T08:15:44Z","snapshot_observed_at":"2026-07-06T17:58:52.016903Z","submitted_at":"2024-04-11T13:36:29Z","title":"ResearchAgent: Iterative Research Idea Generation over Scientific Literature with Large Language Models","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2404.07738","snapshot_observed_at":"2026-08-06T04:16:43.215897Z","title":"arXiv preprint arXiv:2404.07738 , year =","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2608.05144","last_updated":"2026-08-05T17:58:58Z","snapshot_observed_at":"2026-08-09T05:03:12.844436Z","submitted_at":"2026-08-05T17:58:58Z","title":"Argus: A General-Purpose Agentic Runtime for Long-Horizon Reasoning","version":1},"reference_index":11,"source":"arxiv_source","source_observed_at":"2026-08-06T04:16:43.215897Z"},"links":{"cited_paper":"/paper/2404.07738","citing_paper":"/paper/2608.05144"},"observation_digest":"sha256:80a8b1406cd5e714fc03c7c4193e1b9bc05faba5ab461aa0df542d01ebbb87e0","observation_id":"2fead38d-4e8f-494d-a5a0-66acd05cf121","resolution":{"observed_at":"2026-08-06T04:16:43.215897Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2404.07738/citation-record","integrity":"/paper/2404.07738/integrity","json":"/paper/2404.07738/citation-record.json","paper":"/paper/2404.07738"},"outbound":[],"paper":{"arxiv_id":"2404.07738","last_updated":"2025-02-09T08:15:44Z","latest_version":2,"primary_category":"cs.CL","snapshot_observed_at":"2026-07-06T17:58:52.016903Z","submitted_at":"2024-04-11T13:36:29Z","title":"ResearchAgent: Iterative Research Idea Generation over Scientific Literature with Large Language Models"},"reference_resolution":{"displayed":0,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":0,"verified_exact":0,"verified_fuzzy":0},"total_outbound_references":0},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"thesis":"As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 49 inbound Pith citation observations for arXiv:2404.07738."}