{"as_of":"2026-08-19T05:04:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:f7fc2456a089c5a65009094f3bda9cffd5d987ad14671da19dccfad471d6214d","coverage":[{"denominator":46,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":46,"source":"paper_references, paper_reference_links","source_observed_at":"2026-07-13T04:47:57.575546Z","state":"measured"},{"denominator":46,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":46,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-18T06:34:40.430872+00:00","state":"measured"},{"denominator":0,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"cited_works","source_observed_at":null,"state":"measured"}],"external_citation_measurements":[],"inbound":[],"links":{"evidence":"/evidence","html":"/paper/2607.09195/citation-record","integrity":"/paper/2607.09195/integrity","json":"/paper/2607.09195/citation-record.json","paper":"/paper/2607.09195"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-07-13T04:47:57.575546Z","title":"Towardsend-to-endautomationofairesearch.Nature,651(8107):914–919, 2026","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2607.09195","last_updated":"2026-07-10T08:39:30Z","snapshot_observed_at":"2026-08-19T01:37:26.192192Z","submitted_at":"2026-07-10T08:39:30Z","title":"Toward Auditable AI Scientists: A Hypothesis Evolution Protocol for LLM Agents","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-07-13T04:47:57.575546Z"},"links":{"citing_paper":"/paper/2607.09195"},"observation_digest":"sha256:414f15de824eedb62477e0f936842054fe3fc454d6e3949c6938c9f453ea700f","observation_id":"8772dd0d-7198-44a0-b982-f4b30fdddb21","resolution":{"observed_at":"2026-07-13T04:47:57.575546Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2502.18864","last_updated":"2025-02-26T06:17:13Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-02-26T06:17:13Z","title":"Towards an AI co-scientist","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2502.18864","snapshot_observed_at":"2026-07-13T04:47:57.575546Z","title":"Accelerating scientific discovery with co-scientist.Nature, 2026","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2607.09195","last_updated":"2026-07-10T08:39:30Z","snapshot_observed_at":"2026-08-19T01:37:26.192192Z","submitted_at":"2026-07-10T08:39:30Z","title":"Toward Auditable AI Scientists: A Hypothesis Evolution Protocol for LLM Agents","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-07-13T04:47:57.575546Z"},"links":{"cited_paper":"/paper/2502.18864","citing_paper":"/paper/2607.09195"},"observation_digest":"sha256:eb7183de1f9aa9ca2fb4d8133f6d17033ce683d47a31b0d32cd4177ba2e54b1b","observation_id":"e6ba0094-0a0b-48e4-baad-122ccff560a1","resolution":{"observed_at":"2026-07-13T04:47:57.575546Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2511.02824","last_updated":"2025-11-05T18:26:43Z","snapshot_observed_at":"2026-08-17T03:14:20.962319Z","submitted_at":"2025-11-04T18:50:52Z","title":"Kosmos: An AI Scientist for Autonomous Discovery","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2511.02824","snapshot_observed_at":"2026-07-13T04:47:57.575546Z","title":"Landsness, Daniel L","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.09195","last_updated":"2026-07-10T08:39:30Z","snapshot_observed_at":"2026-08-19T01:37:26.192192Z","submitted_at":"2026-07-10T08:39:30Z","title":"Toward Auditable AI Scientists: A Hypothesis Evolution Protocol for LLM Agents","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-07-13T04:47:57.575546Z"},"links":{"cited_paper":"/paper/2511.02824","citing_paper":"/paper/2607.09195"},"observation_digest":"sha256:4c3ea5770605948058b7a0e0d9d71ec470cbc6c69014b06a7de2f958b49e85fc","observation_id":"842b9155-f8c5-47a4-b344-8defde571cd4","resolution":{"observed_at":"2026-07-13T04:47:57.575546Z","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":"2026-07-13T04:47:57.575546Z","title":"Towards agentic intelligence for materials science","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2607.09195","last_updated":"2026-07-10T08:39:30Z","snapshot_observed_at":"2026-08-19T01:37:26.192192Z","submitted_at":"2026-07-10T08:39:30Z","title":"Toward Auditable AI Scientists: A Hypothesis Evolution Protocol for LLM Agents","version":1},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-07-13T04:47:57.575546Z"},"links":{"citing_paper":"/paper/2607.09195"},"observation_digest":"sha256:74f494fd0e9dcb7fb21b150a006216f32014c2759b3f1a47094ed9e0709734cb","observation_id":"c134605c-790f-48d4-be79-ed3272859286","resolution":{"observed_at":"2026-07-13T04:47:57.575546Z","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":"2026-07-13T04:47:57.575546Z","title":"React: Synergizing reasoning and acting in language models","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.09195","last_updated":"2026-07-10T08:39:30Z","snapshot_observed_at":"2026-08-19T01:37:26.192192Z","submitted_at":"2026-07-10T08:39:30Z","title":"Toward Auditable AI Scientists: A Hypothesis Evolution Protocol for LLM Agents","version":1},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-07-13T04:47:57.575546Z"},"links":{"citing_paper":"/paper/2607.09195"},"observation_digest":"sha256:9bd782e104dbcac60e664e180fadd927af2f591315c5e5cf6db3da7b03425482","observation_id":"a805fa02-f56a-43bc-9164-b37e10def821","resolution":{"observed_at":"2026-07-13T04:47:57.575546Z","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":"2026-07-13T04:47:57.575546Z","title":"Introducing the Model Context Protocol.https://www.anthropic.com/news/ model-context-protocol, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.09195","last_updated":"2026-07-10T08:39:30Z","snapshot_observed_at":"2026-08-19T01:37:26.192192Z","submitted_at":"2026-07-10T08:39:30Z","title":"Toward Auditable AI Scientists: A Hypothesis Evolution Protocol for LLM Agents","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-07-13T04:47:57.575546Z"},"links":{"citing_paper":"/paper/2607.09195"},"observation_digest":"sha256:e76ef16bddc949528488826d2c6a0d838a0dfc9a29bfe69e7540389eb12a1699","observation_id":"fb6575c0-3934-42b0-9ede-6567a6120ee8","resolution":{"observed_at":"2026-07-13T04:47:57.575546Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2503.23278","last_updated":"2025-10-07T07:13:32Z","snapshot_observed_at":"2026-08-14T03:34:08.418318Z","submitted_at":"2025-03-30T01:58:22Z","title":"Model Context Protocol (MCP): Landscape, Security Threats, and Future Research Directions","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2503.23278","snapshot_observed_at":"2026-07-13T04:47:57.575546Z","title":"Model context protocol (mcp): Landscape, security threats, and future research directions.arXiv preprint arXiv:2503.23278, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.09195","last_updated":"2026-07-10T08:39:30Z","snapshot_observed_at":"2026-08-19T01:37:26.192192Z","submitted_at":"2026-07-10T08:39:30Z","title":"Toward Auditable AI Scientists: A Hypothesis Evolution Protocol for LLM Agents","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-07-13T04:47:57.575546Z"},"links":{"cited_paper":"/paper/2503.23278","citing_paper":"/paper/2607.09195"},"observation_digest":"sha256:4bcb7ad6fc1d0fffe7811ed499507a519a18ebfce1486b2a5591afcb03dbff9e","observation_id":"6014a6be-dfcb-4f38-ab99-cd0f15cbae09","resolution":{"observed_at":"2026-07-13T04:47:57.575546Z","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":"2026-07-13T04:47:57.575546Z","title":"Voyager: An open-ended embodied agent with large language models.Transactions on Machine Learning Research (TMLR), 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.09195","last_updated":"2026-07-10T08:39:30Z","snapshot_observed_at":"2026-08-19T01:37:26.192192Z","submitted_at":"2026-07-10T08:39:30Z","title":"Toward Auditable AI Scientists: A Hypothesis Evolution Protocol for LLM Agents","version":1},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-07-13T04:47:57.575546Z"},"links":{"citing_paper":"/paper/2607.09195"},"observation_digest":"sha256:7c0dcd8eab944895029c31580955b610690225af591b55e610f70a5236e57468","observation_id":"e496fbd0-9a36-4525-893d-ce76fb98b87f","resolution":{"observed_at":"2026-07-13T04:47:57.575546Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2602.20867","last_updated":"2026-02-24T13:11:38Z","snapshot_observed_at":"2026-08-14T19:45:58.327526Z","submitted_at":"2026-02-24T13:11:38Z","title":"SoK: Agentic Skills -- Beyond Tool Use in LLM Agents","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2602.20867","snapshot_observed_at":"2026-07-13T04:47:57.575546Z","title":"Sok: Agentic skills – beyond tool use in llm agents.arXiv preprint arXiv:2602.20867, 2026","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2607.09195","last_updated":"2026-07-10T08:39:30Z","snapshot_observed_at":"2026-08-19T01:37:26.192192Z","submitted_at":"2026-07-10T08:39:30Z","title":"Toward Auditable AI Scientists: A Hypothesis Evolution Protocol for LLM Agents","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-07-13T04:47:57.575546Z"},"links":{"cited_paper":"/paper/2602.20867","citing_paper":"/paper/2607.09195"},"observation_digest":"sha256:ebd0673db392d35d8e339662f0c45687f2645eb082b20ec14fb4f88e1691e1c7","observation_id":"cabedfdf-e8a0-445e-9c88-fe7dc9901547","resolution":{"observed_at":"2026-07-13T04:47:57.575546Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2504.19413","last_updated":"2025-04-28T01:46:35Z","snapshot_observed_at":"2026-08-14T23:23:31.683130Z","submitted_at":"2025-04-28T01:46:35Z","title":"Mem0: Building Production-Ready AI Agents with Scalable Long-Term Memory","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2504.19413","snapshot_observed_at":"2026-07-13T04:47:57.575546Z","title":"Mem0: Building production-ready ai agents with scalable long-term memory.arXiv preprint arXiv:2504.19413, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.09195","last_updated":"2026-07-10T08:39:30Z","snapshot_observed_at":"2026-08-19T01:37:26.192192Z","submitted_at":"2026-07-10T08:39:30Z","title":"Toward Auditable AI Scientists: A Hypothesis Evolution Protocol for LLM Agents","version":1},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-07-13T04:47:57.575546Z"},"links":{"cited_paper":"/paper/2504.19413","citing_paper":"/paper/2607.09195"},"observation_digest":"sha256:c65883874a540bfea31c3e236281e2c51b073f046951e4c477ef84107e2f90c5","observation_id":"54619231-e67c-45cb-8e6a-203671e19b42","resolution":{"observed_at":"2026-07-13T04:47:57.575546Z","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":"2026-07-13T04:47:57.575546Z","title":"A survey of self-evolving agents: What, when, how, and where to evolve on the path to artificial super intelligence.Transactions on Machine Learning Research, 2026","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2607.09195","last_updated":"2026-07-10T08:39:30Z","snapshot_observed_at":"2026-08-19T01:37:26.192192Z","submitted_at":"2026-07-10T08:39:30Z","title":"Toward Auditable AI Scientists: A Hypothesis Evolution Protocol for LLM Agents","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-07-13T04:47:57.575546Z"},"links":{"citing_paper":"/paper/2607.09195"},"observation_digest":"sha256:11a5913f37b317ca78b8ec7d96482063fac5ad42aaef6d9dc13d34c760622860","observation_id":"b9c4bce8-d54c-4a21-82d3-f743d50eac78","resolution":{"observed_at":"2026-07-13T04:47:57.575546Z","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":"2026-07-13T04:47:57.575546Z","title":"Adaplanner: Adaptive planning from feedback with language models","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.09195","last_updated":"2026-07-10T08:39:30Z","snapshot_observed_at":"2026-08-19T01:37:26.192192Z","submitted_at":"2026-07-10T08:39:30Z","title":"Toward Auditable AI Scientists: A Hypothesis Evolution Protocol for LLM Agents","version":1},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-07-13T04:47:57.575546Z"},"links":{"citing_paper":"/paper/2607.09195"},"observation_digest":"sha256:5e4896f17c898ce695ca386f9f0c2fb8d4e2dd6388316d58f3ef614002c37c42","observation_id":"07274e73-a45c-45d7-a600-4ba299346a16","resolution":{"observed_at":"2026-07-13T04:47:57.575546Z","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":"2026-07-13T04:47:57.575546Z","title":"Reflexion: Language agents with verbal reinforcement learning","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.09195","last_updated":"2026-07-10T08:39:30Z","snapshot_observed_at":"2026-08-19T01:37:26.192192Z","submitted_at":"2026-07-10T08:39:30Z","title":"Toward Auditable AI Scientists: A Hypothesis Evolution Protocol for LLM Agents","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-07-13T04:47:57.575546Z"},"links":{"citing_paper":"/paper/2607.09195"},"observation_digest":"sha256:780e6a48008e5151ecdaa98eb921953a3f1c82190fc818f249abd213f676cc48","observation_id":"10331ea4-3f85-4847-90ea-e4ac02ec54b2","resolution":{"observed_at":"2026-07-13T04:47:57.575546Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2606.11926","last_updated":"2026-06-10T10:57:05Z","snapshot_observed_at":"2026-08-09T20:13:04.512653Z","submitted_at":"2026-06-10T10:57:05Z","title":"Toward Generalist Autonomous Research via Hypothesis-Tree Refinement","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2606.11926","snapshot_observed_at":"2026-07-13T04:47:57.575546Z","title":"Toward generalist autonomous research via hypothesis- tree refinement.arXiv preprint arXiv:2606.11926, 2026","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2607.09195","last_updated":"2026-07-10T08:39:30Z","snapshot_observed_at":"2026-08-19T01:37:26.192192Z","submitted_at":"2026-07-10T08:39:30Z","title":"Toward Auditable AI Scientists: A Hypothesis Evolution Protocol for LLM Agents","version":1},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-07-13T04:47:57.575546Z"},"links":{"cited_paper":"/paper/2606.11926","citing_paper":"/paper/2607.09195"},"observation_digest":"sha256:81644afbfb6d927d04724c616d479bc8d172c8ff11b5b6bd35955b4f24018f11","observation_id":"c0ad3597-e855-4609-af88-347b4f1cc2c6","resolution":{"observed_at":"2026-07-13T04:47:57.575546Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2505.13400","last_updated":"2025-05-19T17:36:17Z","snapshot_observed_at":"2026-08-16T07:07:56.502138Z","submitted_at":"2025-05-19T17:36:17Z","title":"Robin: A multi-agent system for automating scientific discovery","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2505.13400","snapshot_observed_at":"2026-07-13T04:47:57.575546Z","title":"Szostkiewicz, Jon M","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.09195","last_updated":"2026-07-10T08:39:30Z","snapshot_observed_at":"2026-08-19T01:37:26.192192Z","submitted_at":"2026-07-10T08:39:30Z","title":"Toward Auditable AI Scientists: A Hypothesis Evolution Protocol for LLM Agents","version":1},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-07-13T04:47:57.575546Z"},"links":{"cited_paper":"/paper/2505.13400","citing_paper":"/paper/2607.09195"},"observation_digest":"sha256:1e911f01472973e6338a32e19f18e391fce765fd8b4d25b2caca9e596c05cee4","observation_id":"3bc1a851-6094-41da-8b3c-cd6c98b0b501","resolution":{"observed_at":"2026-07-13T04:47:57.575546Z","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":"2026-07-13T04:47:57.575546Z","title":"Biodisco: Multi-agent hypothesis generation with dual-mode evidence, iterative feedback and temporal evaluation.arXiv preprint arXiv:2508.01285, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.09195","last_updated":"2026-07-10T08:39:30Z","snapshot_observed_at":"2026-08-19T01:37:26.192192Z","submitted_at":"2026-07-10T08:39:30Z","title":"Toward Auditable AI Scientists: A Hypothesis Evolution Protocol for LLM Agents","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-07-13T04:47:57.575546Z"},"links":{"citing_paper":"/paper/2607.09195"},"observation_digest":"sha256:8ccbf253393cb2227abbafaeb04ad08f6c01494281cce7638fc985c1020233e1","observation_id":"2fefe5d3-3687-472c-a51f-02a0007d43f9","resolution":{"observed_at":"2026-07-13T04:47:57.575546Z","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":"2026-07-13T04:47:57.575546Z","title":"Bran, Sam Cox, Oliver Schilter, Carlo Baldassari, Andrew D","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.09195","last_updated":"2026-07-10T08:39:30Z","snapshot_observed_at":"2026-08-19T01:37:26.192192Z","submitted_at":"2026-07-10T08:39:30Z","title":"Toward Auditable AI Scientists: A Hypothesis Evolution Protocol for LLM Agents","version":1},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-07-13T04:47:57.575546Z"},"links":{"citing_paper":"/paper/2607.09195"},"observation_digest":"sha256:931bb7c8217f1136609e8e33ff8db141958292f0f3b7ad5a32b03f70fea25123","observation_id":"6f0dc820-4a54-4423-aae0-6606587ce839","resolution":{"observed_at":"2026-07-13T04:47:57.575546Z","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":"2026-07-13T04:47:57.575546Z","title":"Boiko, Robert MacKnight, Ben Kline, and Gabe Gomes","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.09195","last_updated":"2026-07-10T08:39:30Z","snapshot_observed_at":"2026-08-19T01:37:26.192192Z","submitted_at":"2026-07-10T08:39:30Z","title":"Toward Auditable AI Scientists: A Hypothesis Evolution Protocol for LLM Agents","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-07-13T04:47:57.575546Z"},"links":{"citing_paper":"/paper/2607.09195"},"observation_digest":"sha256:07237295b2d9568610d4990924d2b77da139b5be68d2d8e5f488cdcf4da39f48","observation_id":"f8d6231a-d8c8-4f83-b242-a7dd2f3861a9","resolution":{"observed_at":"2026-07-13T04:47:57.575546Z","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":"2026-07-13T04:47:57.575546Z","title":"Organa: A robotic assistant for automated chemistry experimentation and characterization.Matter, 8(2):101897, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.09195","last_updated":"2026-07-10T08:39:30Z","snapshot_observed_at":"2026-08-19T01:37:26.192192Z","submitted_at":"2026-07-10T08:39:30Z","title":"Toward Auditable AI Scientists: A Hypothesis Evolution Protocol for LLM Agents","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-07-13T04:47:57.575546Z"},"links":{"citing_paper":"/paper/2607.09195"},"observation_digest":"sha256:a5b63d79b6afa0e7dc489deb2432fecebfb97b1196ca7849550c298eae309a3a","observation_id":"ba40fb13-7b44-4872-802c-1997097fefa6","resolution":{"observed_at":"2026-07-13T04:47:57.575546Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2406.13163","last_updated":"2024-06-19T02:35:02Z","snapshot_observed_at":"2026-08-17T04:38:05.316458Z","submitted_at":"2024-06-19T02:35:02Z","title":"LLMatDesign: Autonomous Materials Discovery with Large Language Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2406.13163","snapshot_observed_at":"2026-07-13T04:47:57.575546Z","title":"Llmatdesign: Autonomousmaterialsdiscoverywith large language models.arXiv preprint arXiv:2406.13163, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.09195","last_updated":"2026-07-10T08:39:30Z","snapshot_observed_at":"2026-08-19T01:37:26.192192Z","submitted_at":"2026-07-10T08:39:30Z","title":"Toward Auditable AI Scientists: A Hypothesis Evolution Protocol for LLM Agents","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-07-13T04:47:57.575546Z"},"links":{"cited_paper":"/paper/2406.13163","citing_paper":"/paper/2607.09195"},"observation_digest":"sha256:016130ed7e4eb01d468638de674e82cc241dd4d200d27693f7a5135461766e2a","observation_id":"71d21728-3b95-4897-b7d5-dcd250cd5fa0","resolution":{"observed_at":"2026-07-13T04:47:57.575546Z","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":"2026-07-13T04:47:57.575546Z","title":"Accelerated inorganic materials design with generative ai agents.Cell Reports Physical Science, 6(12), 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.09195","last_updated":"2026-07-10T08:39:30Z","snapshot_observed_at":"2026-08-19T01:37:26.192192Z","submitted_at":"2026-07-10T08:39:30Z","title":"Toward Auditable AI Scientists: A Hypothesis Evolution Protocol for LLM Agents","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-07-13T04:47:57.575546Z"},"links":{"citing_paper":"/paper/2607.09195"},"observation_digest":"sha256:85e1884d119cfcf523bf0063b7e9ffad6850fd66f0c10bea7f9f43dc53a1ddaf","observation_id":"9d393947-e4dd-44ce-8ffa-50d310fa2b24","resolution":{"observed_at":"2026-07-13T04:47:57.575546Z","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":"2026-07-13T04:47:57.575546Z","title":"Crystalyse: a multi-tool agent for materials design.arXiv preprint arXiv:2512.00977, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.09195","last_updated":"2026-07-10T08:39:30Z","snapshot_observed_at":"2026-08-19T01:37:26.192192Z","submitted_at":"2026-07-10T08:39:30Z","title":"Toward Auditable AI Scientists: A Hypothesis Evolution Protocol for LLM Agents","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-07-13T04:47:57.575546Z"},"links":{"citing_paper":"/paper/2607.09195"},"observation_digest":"sha256:52800b05de8d47679517890371b1c82b48f6e7ea80041d5c0d943be70f9c9d9c","observation_id":"fdb1e145-9fb2-45f2-a898-d8f3ed047fba","resolution":{"observed_at":"2026-07-13T04:47:57.575546Z","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":"2026-07-13T04:47:57.575546Z","title":"Materealize: a multi-agent deliberation system for end-to-end material design and synthesis.arXiv preprint arXiv:2601.15743, 2026","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2607.09195","last_updated":"2026-07-10T08:39:30Z","snapshot_observed_at":"2026-08-19T01:37:26.192192Z","submitted_at":"2026-07-10T08:39:30Z","title":"Toward Auditable AI Scientists: A Hypothesis Evolution Protocol for LLM Agents","version":1},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-07-13T04:47:57.575546Z"},"links":{"citing_paper":"/paper/2607.09195"},"observation_digest":"sha256:d9279b4e0e6758245a0afcb9684cdd65a959292b1b45d4940f90b6c949703231","observation_id":"7238e51a-a3cc-4906-bd0b-387310955982","resolution":{"observed_at":"2026-07-13T04:47:57.575546Z","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":"2026-07-13T04:47:57.575546Z","title":"El agente: An autonomous agent for quantum chemistry.Matter, 8(7):102263, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.09195","last_updated":"2026-07-10T08:39:30Z","snapshot_observed_at":"2026-08-19T01:37:26.192192Z","submitted_at":"2026-07-10T08:39:30Z","title":"Toward Auditable AI Scientists: A Hypothesis Evolution Protocol for LLM Agents","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-07-13T04:47:57.575546Z"},"links":{"citing_paper":"/paper/2607.09195"},"observation_digest":"sha256:6257385a17edbd7a9fd53f5a0cfdd813d0ddf4587d564893df5193f5111fc12d","observation_id":"a2e4ba77-5cff-433a-a82d-b3e608eb19a2","resolution":{"observed_at":"2026-07-13T04:47:57.575546Z","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":"2026-07-13T04:47:57.575546Z","title":"Pham, Aditya Tanikanti, and Murat Keçeli","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2607.09195","last_updated":"2026-07-10T08:39:30Z","snapshot_observed_at":"2026-08-19T01:37:26.192192Z","submitted_at":"2026-07-10T08:39:30Z","title":"Toward Auditable AI Scientists: A Hypothesis Evolution Protocol for LLM Agents","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-07-13T04:47:57.575546Z"},"links":{"citing_paper":"/paper/2607.09195"},"observation_digest":"sha256:6fa001193d849a9b5274118029ea3c71d69cd15ba7c6844cb6d43e30f02f3054","observation_id":"98c407c6-35e3-4daf-b0a7-2f0c187b9f46","resolution":{"observed_at":"2026-07-13T04:47:57.575546Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2605.24002","last_updated":"2026-05-18T21:45:36Z","snapshot_observed_at":"2026-08-16T14:58:24.551678Z","submitted_at":"2026-05-18T21:45:36Z","title":"Harnessing AtomisticSkills for Agentic Atomistic Research","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2605.24002","snapshot_observed_at":"2026-07-13T04:47:57.575546Z","title":"Harnessing atomisticskills for agentic atomistic research.arXiv preprint arXiv:2605.24002, 2026","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2607.09195","last_updated":"2026-07-10T08:39:30Z","snapshot_observed_at":"2026-08-19T01:37:26.192192Z","submitted_at":"2026-07-10T08:39:30Z","title":"Toward Auditable AI Scientists: A Hypothesis Evolution Protocol for LLM Agents","version":1},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-07-13T04:47:57.575546Z"},"links":{"cited_paper":"/paper/2605.24002","citing_paper":"/paper/2607.09195"},"observation_digest":"sha256:b652242163ccec198d6a34302daec39199544570986f6e7c33cbbf8c87167559","observation_id":"ca4a3b73-69d0-43b2-8a61-50a25e71be3d","resolution":{"observed_at":"2026-07-13T04:47:57.575546Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2604.11957","last_updated":"2026-04-13T18:49:12Z","snapshot_observed_at":"2026-08-17T14:42:40.394234Z","submitted_at":"2026-04-13T18:49:12Z","title":"Agentic LLM Reasoning in a Self-Driving Laboratory for Air-Sensitive Lithium Halide Spinel Conductors","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2604.11957","snapshot_observed_at":"2026-07-13T04:47:57.575546Z","title":"Agenticllmreasoninginaself-driving laboratory for air-sensitive lithium halide spinel conductors.arXiv preprint arXiv:2604.11957, 2026","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2607.09195","last_updated":"2026-07-10T08:39:30Z","snapshot_observed_at":"2026-08-19T01:37:26.192192Z","submitted_at":"2026-07-10T08:39:30Z","title":"Toward Auditable AI Scientists: A Hypothesis Evolution Protocol for LLM Agents","version":1},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-07-13T04:47:57.575546Z"},"links":{"cited_paper":"/paper/2604.11957","citing_paper":"/paper/2607.09195"},"observation_digest":"sha256:eeb7bec7b223327f90bc91ffad51c7172727337cf4c36cad1f5e76b283b83df0","observation_id":"fe25d623-5e79-4fcf-9a02-2e2a822b1265","resolution":{"observed_at":"2026-07-13T04:47:57.575546Z","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":"2026-07-13T04:47:57.575546Z","title":"Performance of ai agents based on reasoning language models on ald process optimization tasks.arXiv preprint arXiv:2601.09980, 2026","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2607.09195","last_updated":"2026-07-10T08:39:30Z","snapshot_observed_at":"2026-08-19T01:37:26.192192Z","submitted_at":"2026-07-10T08:39:30Z","title":"Toward Auditable AI Scientists: A Hypothesis Evolution Protocol for LLM Agents","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-07-13T04:47:57.575546Z"},"links":{"citing_paper":"/paper/2607.09195"},"observation_digest":"sha256:a98e8ed0d54531f70e2e7e9bbe06d7f164ed01da4e015f67f82f8eb6857b0eb1","observation_id":"619d3e21-319f-49fc-a350-955d30f5d928","resolution":{"observed_at":"2026-07-13T04:47:57.575546Z","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":"2026-07-13T04:47:57.575546Z","title":"Knowledge-driven autonomous materials research via collaborative multi-agent and robotic system.Matter, 9(2):102577, 2026","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2607.09195","last_updated":"2026-07-10T08:39:30Z","snapshot_observed_at":"2026-08-19T01:37:26.192192Z","submitted_at":"2026-07-10T08:39:30Z","title":"Toward Auditable AI Scientists: A Hypothesis Evolution Protocol for LLM Agents","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-07-13T04:47:57.575546Z"},"links":{"citing_paper":"/paper/2607.09195"},"observation_digest":"sha256:e5cbac293b3d0a7298c0175d73858a85a90ce3d9e5bb8d5611da6793755d28f8","observation_id":"962a7ab6-3b09-434b-a58e-db99bf0a27da","resolution":{"observed_at":"2026-07-13T04:47:57.575546Z","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":"2026-07-13T04:47:57.575546Z","title":"Smedskjaer, Katrin Wondraczek, Lothar Wondraczek, Nitya Nand Gosvami, and N","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.09195","last_updated":"2026-07-10T08:39:30Z","snapshot_observed_at":"2026-08-19T01:37:26.192192Z","submitted_at":"2026-07-10T08:39:30Z","title":"Toward Auditable AI Scientists: A Hypothesis Evolution Protocol for LLM Agents","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-07-13T04:47:57.575546Z"},"links":{"citing_paper":"/paper/2607.09195"},"observation_digest":"sha256:63acd48cb543f24554219846adef3acb0f645010d8246802d153a33a6d2df3f4","observation_id":"810f0008-9654-44ed-9d91-e4f279a9c84c","resolution":{"observed_at":"2026-07-13T04:47:57.575546Z","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":"2026-07-13T04:47:57.575546Z","title":"Prince, Tao Zhou, Henry Chan, and Mathew J","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2607.09195","last_updated":"2026-07-10T08:39:30Z","snapshot_observed_at":"2026-08-19T01:37:26.192192Z","submitted_at":"2026-07-10T08:39:30Z","title":"Toward Auditable AI Scientists: A Hypothesis Evolution Protocol for LLM Agents","version":1},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-07-13T04:47:57.575546Z"},"links":{"citing_paper":"/paper/2607.09195"},"observation_digest":"sha256:d9bd80c54d86fd684a1cfe28790b7a15333d8e5d5e61997e4f7d41310b3f33b1","observation_id":"9b9a5c5c-1f53-488d-b691-7d4b8a8fd285","resolution":{"observed_at":"2026-07-13T04:47:57.575546Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2604.18805","last_updated":"2026-04-20T20:23:42Z","snapshot_observed_at":"2026-08-11T12:30:36.819624Z","submitted_at":"2026-04-20T20:23:42Z","title":"AI scientists produce results without reasoning scientifically","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2604.18805","snapshot_observed_at":"2026-07-13T04:47:57.575546Z","title":"Aiscientistsproduce results without reasoning scientifically.arXiv preprint arXiv:2604.18805, 2026","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2607.09195","last_updated":"2026-07-10T08:39:30Z","snapshot_observed_at":"2026-08-19T01:37:26.192192Z","submitted_at":"2026-07-10T08:39:30Z","title":"Toward Auditable AI Scientists: A Hypothesis Evolution Protocol for LLM Agents","version":1},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-07-13T04:47:57.575546Z"},"links":{"cited_paper":"/paper/2604.18805","citing_paper":"/paper/2607.09195"},"observation_digest":"sha256:5765211678d052ee526afd008f0f258aac00458ea83dc33a1141186dad4e2622","observation_id":"46b01d9a-63ca-4606-9809-8b74927654c0","resolution":{"observed_at":"2026-07-13T04:47:57.575546Z","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":"2026-07-13T04:47:57.575546Z","title":null,"venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.09195","last_updated":"2026-07-10T08:39:30Z","snapshot_observed_at":"2026-08-19T01:37:26.192192Z","submitted_at":"2026-07-10T08:39:30Z","title":"Toward Auditable AI Scientists: A Hypothesis Evolution Protocol for LLM Agents","version":1},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-07-13T04:47:57.575546Z"},"links":{"citing_paper":"/paper/2607.09195"},"observation_digest":"sha256:dd477a4e9f1bb71ceb857181b1f41170b3287c700fe17361d19f26d96fde8811","observation_id":"efb784d4-d6d1-4535-b4b1-80de0c01386e","resolution":{"observed_at":"2026-07-13T04:47:57.575546Z","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":"2026-07-13T04:47:57.575546Z","title":"Large language models for automated open-domain scientific hypotheses discovery","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.09195","last_updated":"2026-07-10T08:39:30Z","snapshot_observed_at":"2026-08-19T01:37:26.192192Z","submitted_at":"2026-07-10T08:39:30Z","title":"Toward Auditable AI Scientists: A Hypothesis Evolution Protocol for LLM Agents","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-07-13T04:47:57.575546Z"},"links":{"citing_paper":"/paper/2607.09195"},"observation_digest":"sha256:cb33b32a1ce7c93cc7e47a0c28772c4c311bdfbd9e9227555416cb550bb3ecc4","observation_id":"795fd306-c083-42b3-b0e2-0cd13d381e1b","resolution":{"observed_at":"2026-07-13T04:47:57.575546Z","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":"2026-07-13T04:47:57.575546Z","title":"Moose-chem: Large language models for rediscovering unseen chemistry scientific hypotheses","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.09195","last_updated":"2026-07-10T08:39:30Z","snapshot_observed_at":"2026-08-19T01:37:26.192192Z","submitted_at":"2026-07-10T08:39:30Z","title":"Toward Auditable AI Scientists: A Hypothesis Evolution Protocol for LLM Agents","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-07-13T04:47:57.575546Z"},"links":{"citing_paper":"/paper/2607.09195"},"observation_digest":"sha256:0bed638a2ff60bdb4ab859eb397e20ef003886d0fef91f6e3b6d61e1283aa593","observation_id":"ec334b22-e6d8-4dfc-8531-5cf8b3333cb0","resolution":{"observed_at":"2026-07-13T04:47:57.575546Z","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":"2026-07-13T04:47:57.575546Z","title":"Moose-chem2: Exploringllmlimitsinfine-grainedscien- tific hypothesis discovery via hierarchical search","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.09195","last_updated":"2026-07-10T08:39:30Z","snapshot_observed_at":"2026-08-19T01:37:26.192192Z","submitted_at":"2026-07-10T08:39:30Z","title":"Toward Auditable AI Scientists: A Hypothesis Evolution Protocol for LLM Agents","version":1},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-07-13T04:47:57.575546Z"},"links":{"citing_paper":"/paper/2607.09195"},"observation_digest":"sha256:4a61e53ad7085706a9db3b7ee2f160fdf05f60309dc5520fae11bb14af489139","observation_id":"194876a0-22cb-4e38-895c-4dfb4a107f74","resolution":{"observed_at":"2026-07-13T04:47:57.575546Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2411.11910","last_updated":"2024-11-24T12:59:44Z","snapshot_observed_at":"2026-08-18T03:56:12.036803Z","submitted_at":"2024-11-17T13:40:35Z","title":"AIGS: Generating Science from AI-Powered Automated Falsification","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2411.11910","snapshot_observed_at":"2026-07-13T04:47:57.575546Z","title":"Aigs: Generating science from ai-powered automated falsification.arXiv preprint arXiv:2411.11910, 2024","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2607.09195","last_updated":"2026-07-10T08:39:30Z","snapshot_observed_at":"2026-08-19T01:37:26.192192Z","submitted_at":"2026-07-10T08:39:30Z","title":"Toward Auditable AI Scientists: A Hypothesis Evolution Protocol for LLM Agents","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-07-13T04:47:57.575546Z"},"links":{"cited_paper":"/paper/2411.11910","citing_paper":"/paper/2607.09195"},"observation_digest":"sha256:a7784e875066946170b8122f729a80073fb669eeafe8af28fd754512d1a9ee24","observation_id":"ab0ad8b7-e9a9-4707-a120-85d61c7eff45","resolution":{"observed_at":"2026-07-13T04:47:57.575546Z","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":"2026-07-13T04:47:57.575546Z","title":"Li, Emmanuel Candès, and Jure Leskovec","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.09195","last_updated":"2026-07-10T08:39:30Z","snapshot_observed_at":"2026-08-19T01:37:26.192192Z","submitted_at":"2026-07-10T08:39:30Z","title":"Toward Auditable AI Scientists: A Hypothesis Evolution Protocol for LLM Agents","version":1},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-07-13T04:47:57.575546Z"},"links":{"citing_paper":"/paper/2607.09195"},"observation_digest":"sha256:102c6727e694d0ee0af5c9a8dfcae0c9ae4c2b51040291d1c60c54ec709d7b7a","observation_id":"35a79b55-609b-4891-8428-857e73433551","resolution":{"observed_at":"2026-07-13T04:47:57.575546Z","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":"2026-07-13T04:47:57.575546Z","title":"Autodiscovery: Open-ended scientific discovery via bayesian surprise","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.09195","last_updated":"2026-07-10T08:39:30Z","snapshot_observed_at":"2026-08-19T01:37:26.192192Z","submitted_at":"2026-07-10T08:39:30Z","title":"Toward Auditable AI Scientists: A Hypothesis Evolution Protocol for LLM Agents","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-07-13T04:47:57.575546Z"},"links":{"citing_paper":"/paper/2607.09195"},"observation_digest":"sha256:aecfb65588a06cb83f3cd67de87b79b24d413bc8586641fbb8e792d4135964df","observation_id":"fedc48a9-4baa-4fe5-9a1c-613fb490efee","resolution":{"observed_at":"2026-07-13T04:47:57.575546Z","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":"2026-07-13T04:47:57.575546Z","title":"Wang, Lee Marom, Subhadeep Pal, Rachel K","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2607.09195","last_updated":"2026-07-10T08:39:30Z","snapshot_observed_at":"2026-08-19T01:37:26.192192Z","submitted_at":"2026-07-10T08:39:30Z","title":"Toward Auditable AI Scientists: A Hypothesis Evolution Protocol for LLM Agents","version":1},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-07-13T04:47:57.575546Z"},"links":{"citing_paper":"/paper/2607.09195"},"observation_digest":"sha256:0d4e69a1a82d80ed85d49013d6247ed375b6f044d4a06ee70710bd0d5856451b","observation_id":"d006a7ba-2e4e-4e45-bae5-b724590774e0","resolution":{"observed_at":"2026-07-13T04:47:57.575546Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2605.26087","last_updated":"2026-05-25T17:50:07Z","snapshot_observed_at":"2026-07-06T23:36:01.564747Z","submitted_at":"2026-05-25T17:50:07Z","title":"DiscoverPhysics: Benchmarking LLMs for Out-of-the-Box Scientific Thinking","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2605.26087","snapshot_observed_at":"2026-07-13T04:47:57.575546Z","title":"Discoverphysics: Benchmarking llms for out-of-the-box scientific thinking.arXiv preprint arXiv:2605.26087, 2026","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2607.09195","last_updated":"2026-07-10T08:39:30Z","snapshot_observed_at":"2026-08-19T01:37:26.192192Z","submitted_at":"2026-07-10T08:39:30Z","title":"Toward Auditable AI Scientists: A Hypothesis Evolution Protocol for LLM Agents","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-07-13T04:47:57.575546Z"},"links":{"cited_paper":"/paper/2605.26087","citing_paper":"/paper/2607.09195"},"observation_digest":"sha256:e3f6beb525c0ce2498d2137434a5993cb9eb6381e50c017c187a9c0054b6467d","observation_id":"fb882f91-c4da-4fd1-8c92-563b07b1fa1d","resolution":{"observed_at":"2026-07-13T04:47:57.575546Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2605.26200","last_updated":"2026-05-25T17:16:52Z","snapshot_observed_at":"2026-08-02T15:58:39.229575Z","submitted_at":"2026-05-25T17:16:52Z","title":"Workflow Closure Is Not Scientific Closure in Auto-Research Systems","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2605.26200","snapshot_observed_at":"2026-07-13T04:47:57.575546Z","title":"Workflow closure is not scientific closure in auto-research systems.arXiv preprint arXiv:2605.26200, 2026","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2607.09195","last_updated":"2026-07-10T08:39:30Z","snapshot_observed_at":"2026-08-19T01:37:26.192192Z","submitted_at":"2026-07-10T08:39:30Z","title":"Toward Auditable AI Scientists: A Hypothesis Evolution Protocol for LLM Agents","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-07-13T04:47:57.575546Z"},"links":{"cited_paper":"/paper/2605.26200","citing_paper":"/paper/2607.09195"},"observation_digest":"sha256:5debc397baa771705db1c5a76e9bf1afaedf4818fcd397c3b324d76eab3d49e6","observation_id":"37b94a76-29f1-46f1-bb77-bd6bbb7888b1","resolution":{"observed_at":"2026-07-13T04:47:57.575546Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2605.08956","last_updated":"2026-05-09T13:52:23Z","snapshot_observed_at":"2026-08-11T14:00:28.517768Z","submitted_at":"2026-05-09T13:52:23Z","title":"Agentic AI Scientists Are Not Built For Autonomous Scientific Discovery","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2605.08956","snapshot_observed_at":"2026-07-13T04:47:57.575546Z","title":null,"venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2607.09195","last_updated":"2026-07-10T08:39:30Z","snapshot_observed_at":"2026-08-19T01:37:26.192192Z","submitted_at":"2026-07-10T08:39:30Z","title":"Toward Auditable AI Scientists: A Hypothesis Evolution Protocol for LLM Agents","version":1},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-07-13T04:47:57.575546Z"},"links":{"cited_paper":"/paper/2605.08956","citing_paper":"/paper/2607.09195"},"observation_digest":"sha256:8a731c1742a986e5fed9e761f95fcb62588ae3a7aa5b2ffea17381475cbc20c0","observation_id":"e4b59e4f-20ff-44a2-be69-9d881e0e72b5","resolution":{"observed_at":"2026-07-13T04:47:57.575546Z","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":"2026-07-13T04:47:57.575546Z","title":"GPT-5.5 System Card.https://openai.com/index/gpt-5-5-system-card/, 2026","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2607.09195","last_updated":"2026-07-10T08:39:30Z","snapshot_observed_at":"2026-08-19T01:37:26.192192Z","submitted_at":"2026-07-10T08:39:30Z","title":"Toward Auditable AI Scientists: A Hypothesis Evolution Protocol for LLM Agents","version":1},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-07-13T04:47:57.575546Z"},"links":{"citing_paper":"/paper/2607.09195"},"observation_digest":"sha256:2059bde84a10e1a3bdcc26267951116fa4abc89245a1f3615f9e43bf60ccb260","observation_id":"dfc32ef9-3976-47ef-a3b6-b04a1d0c290b","resolution":{"observed_at":"2026-07-13T04:47:57.575546Z","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":"2026-07-13T04:47:57.575546Z","title":"Introducing GPT-5.4 mini and nano.https://openai.com/index/ introducing-gpt-5-4-mini-and-nano/, 2026","venue":null,"work_id":null,"year":2026},"citing_paper":{"arxiv_id":"2607.09195","last_updated":"2026-07-10T08:39:30Z","snapshot_observed_at":"2026-08-19T01:37:26.192192Z","submitted_at":"2026-07-10T08:39:30Z","title":"Toward Auditable AI Scientists: A Hypothesis Evolution Protocol for LLM Agents","version":1},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-07-13T04:47:57.575546Z"},"links":{"citing_paper":"/paper/2607.09195"},"observation_digest":"sha256:228e7e4b8eab135f1327dd1d9f2f56504e67a159e7394691510f590882c9f994","observation_id":"62aa19a0-1faa-435a-a5c3-76444095b30f","resolution":{"observed_at":"2026-07-13T04:47:57.575546Z","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":"2026-07-13T04:47:57.575546Z","title":"Introducing GPT-4.1 in the API.https://openai.com/index/gpt-4-1/, 2025","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2607.09195","last_updated":"2026-07-10T08:39:30Z","snapshot_observed_at":"2026-08-19T01:37:26.192192Z","submitted_at":"2026-07-10T08:39:30Z","title":"Toward Auditable AI Scientists: A Hypothesis Evolution Protocol for LLM Agents","version":1},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-07-13T04:47:57.575546Z"},"links":{"citing_paper":"/paper/2607.09195"},"observation_digest":"sha256:390efae5a3d7e17d340a6481eced81a386644a8a7c2069dd2f333c3c28b2a243","observation_id":"64bf5b7b-5990-4a82-890c-9a2284481275","resolution":{"observed_at":"2026-07-13T04:47:57.575546Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2607.09195","last_updated":"2026-07-10T08:39:30Z","latest_version":1,"primary_category":"cs.AI","snapshot_observed_at":"2026-08-19T01:37:26.192192Z","submitted_at":"2026-07-10T08:39:30Z","title":"Toward Auditable AI Scientists: A Hypothesis Evolution Protocol for LLM Agents"},"reference_resolution":{"displayed":46,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":46,"verified_exact":0,"verified_fuzzy":0},"total_outbound_references":46},"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":"2026-08-18T06:34:40.430872+00:00","source":"crossref"},{"observed_at":"2026-08-18T06:34:34.496301+00:00","source":"retraction_watch"}],"thesis":"As of 19 August 2026, this Paper Citation Record lists 46 of 46 outbound references and 0 inbound Pith citation observations for arXiv:2607.09195."}