{"as_of":"2026-08-09T20:11:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:36f61b99b4b8d9b4b206bbef0702daa7d691b0521c212626d562cbbfa9489447","coverage":[{"denominator":65,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":65,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-07T11:49:08.589917Z","state":"measured"},{"denominator":68,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":68,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-09T06:31:02.800959+00:00","state":"measured"},{"denominator":3,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":3,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-01T12:50:06.841591Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"arxiv_reference","source_observed_at":"2026-05-20T20:03:44.060778Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2506.01372","last_updated":"2025-06-09T09:01:24Z","snapshot_observed_at":"2026-08-09T03:01:37.763836Z","submitted_at":"2025-06-02T06:59:10Z","title":"AI Scientists Fail Without Strong Implementation Capability","version":2},"cited_work":{"arxiv_id":"2506.01372","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2506.01372","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Evaluation conducted exclusively on synthetic datasets","venue":null,"work_id":"0b2c1af8-3ba1-48eb-b5ba-301f7b61d917","year":2025},"citing_paper":{"arxiv_id":"2605.10813","last_updated":"2026-05-11T16:33:47Z","snapshot_observed_at":"2026-07-30T22:58:47.084744Z","submitted_at":"2026-05-11T16:33:47Z","title":"NanoResearch: Co-Evolving Skills, Memory, and Policy for Personalized Research Automation","version":1},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-05-12T04:12:49.742272Z"},"links":{"cited_paper":"/paper/2506.01372","citing_paper":"/paper/2605.10813"},"observation_digest":"sha256:6d8e5f85e4847731bc8c39b5a81921a952801d623124131ee1689ef9fd2ae557","observation_id":"97cfaa6a-2bb8-435e-9301-ba03667c0551","resolution":{"observed_at":"2026-05-12T06:31:27.256386Z","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":"2506.01372","last_updated":"2025-06-09T09:01:24Z","snapshot_observed_at":"2026-08-09T03:01:37.763836Z","submitted_at":"2025-06-02T06:59:10Z","title":"AI Scientists Fail Without Strong Implementation Capability","version":2},"cited_work":{"arxiv_id":"2506.01372","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2506.01372","snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Evaluation conducted exclusively on synthetic datasets","venue":null,"work_id":"0b2c1af8-3ba1-48eb-b5ba-301f7b61d917","year":2025},"citing_paper":{"arxiv_id":"2605.16616","last_updated":"2026-05-15T20:35:32Z","snapshot_observed_at":"2026-07-06T23:27:43.762904Z","submitted_at":"2026-05-15T20:35:32Z","title":"MLReplicate: Benchmarking Autonomous Research Systems for Machine Learning Reproducibility","version":1},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-05-20T19:59:40.519962Z"},"links":{"cited_paper":"/paper/2506.01372","citing_paper":"/paper/2605.16616"},"observation_digest":"sha256:c69bce72de0140f110cea1870fc3c10c5bebd6a81dd015aff218530a7be0de67","observation_id":"f88f855f-8dd1-40e0-8d56-2bd040ecf91c","resolution":{"observed_at":"2026-05-20T20:03:44.063892Z","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":"2506.01372","last_updated":"2025-06-09T09:01:24Z","snapshot_observed_at":"2026-08-09T03:01:37.763836Z","submitted_at":"2025-06-02T06:59:10Z","title":"AI Scientists Fail Without Strong Implementation Capability","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2506.01372","snapshot_observed_at":"2026-08-01T12:50:06.841591Z","title":"2506.01372 , archivePrefix=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.26587","last_updated":"2026-07-29T08:06:43Z","snapshot_observed_at":"2026-08-07T15:35:26.187389Z","submitted_at":"2026-07-29T08:06:43Z","title":"One Run Is Not an Idea: The Implementation Lottery in Automated Research","version":1},"reference_index":27,"source":"arxiv_source","source_observed_at":"2026-08-01T12:50:06.841591Z"},"links":{"cited_paper":"/paper/2506.01372","citing_paper":"/paper/2607.26587"},"observation_digest":"sha256:0252f9e5667f4a0915b19201b10491dc61422148502282a01c9ae511e342811d","observation_id":"86739275-b7ef-446e-9e91-d13888aeffe3","resolution":{"observed_at":"2026-08-01T12:50:06.841591Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2506.01372/citation-record","integrity":"/paper/2506.01372/integrity","json":"/paper/2506.01372/citation-record.json","paper":"/paper/2506.01372"},"outbound":[{"citation":{"cited_paper":{"arxiv_id":"2502.15631","last_updated":"2026-07-07T09:54:57Z","snapshot_observed_at":"2026-08-07T17:57:53.478530Z","submitted_at":"2025-02-21T17:59:13Z","title":"The relationship between reasoning and performance in large language models--o3 (mini) thinks harder, not longer","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2502.15631","snapshot_observed_at":"2026-08-07T11:49:00.983368Z","title":"The relationship between reasoning and performance in large language models–o3 (mini) thinks harder, not longer.arXiv preprint arXiv:2502.15631,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.01372","last_updated":"2025-06-09T09:01:24Z","snapshot_observed_at":"2026-08-09T03:01:37.763836Z","submitted_at":"2025-06-02T06:59:10Z","title":"AI Scientists Fail Without Strong Implementation Capability","version":2},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-08-07T11:49:00.983368Z"},"links":{"cited_paper":"/paper/2502.15631","citing_paper":"/paper/2506.01372"},"observation_digest":"sha256:252f010628ab07a35dc9c7879e368088479b854a886b1014a5ca8df239c3fd94","observation_id":"585cbaa4-8e54-47fb-9164-e43527107246","resolution":{"observed_at":"2026-08-07T11:49:00.983368Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2502.15657","last_updated":"2025-02-24T18:14:15Z","snapshot_observed_at":"2026-08-08T14:17:37.842596Z","submitted_at":"2025-02-21T18:28:36Z","title":"Superintelligent Agents Pose Catastrophic Risks: Can Scientist AI Offer a Safer Path?","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2502.15657","snapshot_observed_at":"2026-08-07T11:49:01.121192Z","title":"Superintelligent agents pose catastrophic risks: Can scientist ai offer a safer path?arXiv preprint arXiv:2502.15657,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.01372","last_updated":"2025-06-09T09:01:24Z","snapshot_observed_at":"2026-08-09T03:01:37.763836Z","submitted_at":"2025-06-02T06:59:10Z","title":"AI Scientists Fail Without Strong Implementation Capability","version":2},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-08-07T11:49:01.121192Z"},"links":{"cited_paper":"/paper/2502.15657","citing_paper":"/paper/2506.01372"},"observation_digest":"sha256:c254116330f92a3050139acf2df16a1cbb08caccbff1c87f8395c1bbf3f06524","observation_id":"455fb266-b19a-4eb2-9f40-29ccbf107ead","resolution":{"observed_at":"2026-08-07T11:49:01.121192Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2503.13657","last_updated":"2025-10-26T23:25:18Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-03-17T19:04:38Z","title":"Why Do Multi-Agent LLM Systems Fail?","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2503.13657","snapshot_observed_at":"2026-08-07T11:49:01.392416Z","title":"Why do multi-agent llm systems fail?arXiv preprint arXiv:2503.13657,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.01372","last_updated":"2025-06-09T09:01:24Z","snapshot_observed_at":"2026-08-09T03:01:37.763836Z","submitted_at":"2025-06-02T06:59:10Z","title":"AI Scientists Fail Without Strong Implementation Capability","version":2},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-08-07T11:49:01.392416Z"},"links":{"cited_paper":"/paper/2503.13657","citing_paper":"/paper/2506.01372"},"observation_digest":"sha256:14142b5f3981ef60f40719c3b2aa48d62cbfeddb96da855f325a44366348679d","observation_id":"6207316a-2237-4f4b-a5fe-c563dc2dee76","resolution":{"observed_at":"2026-08-07T11:49:01.392416Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.07095","last_updated":"2025-02-26T11:57:30Z","snapshot_observed_at":"2026-08-06T21:08:58.653035Z","submitted_at":"2024-10-09T17:34:27Z","title":"MLE-bench: Evaluating Machine Learning Agents on Machine Learning Engineering","version":6},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.07095","snapshot_observed_at":"2026-08-07T11:49:01.526190Z","title":"Mle-bench: Evaluating machine learning agents on machine learning engineering.arXiv preprint arXiv:2410.07095,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.01372","last_updated":"2025-06-09T09:01:24Z","snapshot_observed_at":"2026-08-09T03:01:37.763836Z","submitted_at":"2025-06-02T06:59:10Z","title":"AI Scientists Fail Without Strong Implementation Capability","version":2},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-07T11:49:01.526190Z"},"links":{"cited_paper":"/paper/2410.07095","citing_paper":"/paper/2506.01372"},"observation_digest":"sha256:ebdbf145c3e212d8eb94774cd2b94bbe39b1cba469ab540c89abe5fcb2889400","observation_id":"089f937e-d284-4d45-9032-4f160e40483b","resolution":{"observed_at":"2026-08-07T11:49:01.526190Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2107.03374","last_updated":"2021-07-14T17:16:02Z","snapshot_observed_at":"2026-08-08T11:58:24.516369Z","submitted_at":"2021-07-07T17:41:24Z","title":"Evaluating Large Language Models Trained on Code","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2107.03374","snapshot_observed_at":"2026-08-07T11:49:01.642722Z","title":"doi: 10.1145/3641289","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.01372","last_updated":"2025-06-09T09:01:24Z","snapshot_observed_at":"2026-08-09T03:01:37.763836Z","submitted_at":"2025-06-02T06:59:10Z","title":"AI Scientists Fail Without Strong Implementation Capability","version":2},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-08-07T11:49:01.642722Z"},"links":{"cited_paper":"/paper/2107.03374","citing_paper":"/paper/2506.01372"},"observation_digest":"sha256:b8895d3534ad67a3658ec983c7e274614e9e38b773e8945c1d3c681fd80c72c2","observation_id":"876f5b07-7c47-418d-aa72-f9fd5c158357","resolution":{"observed_at":"2026-08-07T11:49:01.642722Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2109.09774","last_updated":"2021-09-20T18:06:22Z","snapshot_observed_at":"2026-07-06T11:49:38.497583Z","submitted_at":"2021-09-20T18:06:22Z","title":"Inconsistency in Conference Peer Review: Revisiting the 2014 NeurIPS Experiment","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2109.09774","snapshot_observed_at":"2026-08-07T11:49:01.756223Z","title":"Corinna Cortes and Neil D Lawrence","venue":null,"work_id":null,"year":2014},"citing_paper":{"arxiv_id":"2506.01372","last_updated":"2025-06-09T09:01:24Z","snapshot_observed_at":"2026-08-09T03:01:37.763836Z","submitted_at":"2025-06-02T06:59:10Z","title":"AI Scientists Fail Without Strong Implementation Capability","version":2},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-08-07T11:49:01.756223Z"},"links":{"cited_paper":"/paper/2109.09774","citing_paper":"/paper/2506.01372"},"observation_digest":"sha256:5400b4c7f8b1d7b87061a49b20420b7a54e6fb3d86b9f654ce634c791f9b802b","observation_id":"eacc1515-4c04-404b-8f86-dd730f5c796a","resolution":{"observed_at":"2026-08-07T11:49:01.756223Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2504.16728","last_updated":"2025-05-24T12:40:05Z","snapshot_observed_at":"2026-08-07T15:59:53.514990Z","submitted_at":"2025-04-23T14:01:36Z","title":"IRIS: Interactive Research Ideation System for Accelerating Scientific Discovery","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2504.16728","snapshot_observed_at":"2026-08-07T11:49:01.877094Z","title":"Iris: Interactive research ideation system for accelerating scientific discovery.arXiv preprint arXiv:2504.16728,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.01372","last_updated":"2025-06-09T09:01:24Z","snapshot_observed_at":"2026-08-09T03:01:37.763836Z","submitted_at":"2025-06-02T06:59:10Z","title":"AI Scientists Fail Without Strong Implementation Capability","version":2},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-08-07T11:49:01.877094Z"},"links":{"cited_paper":"/paper/2504.16728","citing_paper":"/paper/2506.01372"},"observation_digest":"sha256:5a0160c2c32f94bef478dd1febb4b62410168acc88f2dc3df8a236a310d398fa","observation_id":"c24984a8-a972-4069-9cd9-29a63c0180ac","resolution":{"observed_at":"2026-08-07T11:49:01.877094Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2409.05556","last_updated":"2024-09-09T12:25:10Z","snapshot_observed_at":"2026-07-06T19:12:27.820454Z","submitted_at":"2024-09-09T12:25:10Z","title":"SciAgents: Automating scientific discovery through multi-agent intelligent graph reasoning","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2409.05556","snapshot_observed_at":"2026-08-07T11:49:02.009902Z","title":"Sciagents: Automating scientific discovery through multi-agent intelligent graph reasoning.arXiv preprint arXiv:2409.05556,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.01372","last_updated":"2025-06-09T09:01:24Z","snapshot_observed_at":"2026-08-09T03:01:37.763836Z","submitted_at":"2025-06-02T06:59:10Z","title":"AI Scientists Fail Without Strong Implementation Capability","version":2},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-07T11:49:02.009902Z"},"links":{"cited_paper":"/paper/2409.05556","citing_paper":"/paper/2506.01372"},"observation_digest":"sha256:d40dc5be0bc4ec806e93fbf5721877f616e2f6c805f58cd72591d3c54fb11299","observation_id":"241d67cb-b175-4b1e-a3be-e5dc6f1f587a","resolution":{"observed_at":"2026-08-07T11:49:02.009902Z","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":"2026-08-07T11:49:02.170925Z","title":"Towards an ai co-scientist.arXiv preprint arXiv:2502.18864,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.01372","last_updated":"2025-06-09T09:01:24Z","snapshot_observed_at":"2026-08-09T03:01:37.763836Z","submitted_at":"2025-06-02T06:59:10Z","title":"AI Scientists Fail Without Strong Implementation Capability","version":2},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-08-07T11:49:02.170925Z"},"links":{"cited_paper":"/paper/2502.18864","citing_paper":"/paper/2506.01372"},"observation_digest":"sha256:37921680e7844b3a3e4e80063b0f83cfe6efaaddb85cb55ee1877d4cf0eb4a64","observation_id":"e2855918-989d-414d-9544-9df08d6fe3ee","resolution":{"observed_at":"2026-08-07T11:49:02.170925Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2412.14141","last_updated":"2025-02-17T04:31:41Z","snapshot_observed_at":"2026-07-06T20:09:28.763595Z","submitted_at":"2024-12-18T18:41:14Z","title":"LLMs can Realize Combinatorial Creativity: Generating Creative Ideas via LLMs for Scientific Research","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2412.14141","snapshot_observed_at":"2026-08-07T11:49:02.277328Z","title":"Llms can realize combinatorial creativity: generating creative ideas via llms for scientific research.arXiv preprint arXiv:2412.14141, 2024a","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.01372","last_updated":"2025-06-09T09:01:24Z","snapshot_observed_at":"2026-08-09T03:01:37.763836Z","submitted_at":"2025-06-02T06:59:10Z","title":"AI Scientists Fail Without Strong Implementation Capability","version":2},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-08-07T11:49:02.277328Z"},"links":{"cited_paper":"/paper/2412.14141","citing_paper":"/paper/2506.01372"},"observation_digest":"sha256:9e80db3b2ce51fd1588920ae15a6b5c612baef2b51e3ae5aaaa55d7100d6d98f","observation_id":"60bd406f-dec0-4d74-b55c-44969e5dc4f0","resolution":{"observed_at":"2026-08-07T11:49:02.277328Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2402.01680","last_updated":"2024-04-19T01:15:16Z","snapshot_observed_at":"2026-08-06T19:10:15.466826Z","submitted_at":"2024-01-21T23:36:14Z","title":"Large Language Model based Multi-Agents: A Survey of Progress and Challenges","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2402.01680","snapshot_observed_at":"2026-08-07T11:49:02.382812Z","title":"Large language model based multi-agents: A survey of progress and challenges.arXiv preprint arXiv:2402.01680,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.01372","last_updated":"2025-06-09T09:01:24Z","snapshot_observed_at":"2026-08-09T03:01:37.763836Z","submitted_at":"2025-06-02T06:59:10Z","title":"AI Scientists Fail Without Strong Implementation Capability","version":2},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-08-07T11:49:02.382812Z"},"links":{"cited_paper":"/paper/2402.01680","citing_paper":"/paper/2506.01372"},"observation_digest":"sha256:c0a44fd449774ccef27b3033a6ce6aca491243ad22611d04cc56d240771d1341","observation_id":"11fd7b30-7776-474d-914b-ffb838c06046","resolution":{"observed_at":"2026-08-07T11:49:02.382812Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2501.10120","last_updated":"2025-05-27T11:01:29Z","snapshot_observed_at":"2026-08-07T16:57:09.949824Z","submitted_at":"2025-01-17T11:12:28Z","title":"PaSa: An LLM Agent for Comprehensive Academic Paper Search","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2501.10120","snapshot_observed_at":"2026-08-07T11:49:02.520844Z","title":"Pasa: An llm agent for comprehensive academic paper search.arXiv preprint arXiv:2501.10120,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.01372","last_updated":"2025-06-09T09:01:24Z","snapshot_observed_at":"2026-08-09T03:01:37.763836Z","submitted_at":"2025-06-02T06:59:10Z","title":"AI Scientists Fail Without Strong Implementation Capability","version":2},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-08-07T11:49:02.520844Z"},"links":{"cited_paper":"/paper/2501.10120","citing_paper":"/paper/2506.01372"},"observation_digest":"sha256:43f4e32165f7e0baecbca62f1606aeb37ae896677619c82c42b6b36f59497caa","observation_id":"cc8fcd72-2d9b-4c9e-9ac9-88fbd7848eca","resolution":{"observed_at":"2026-08-07T11:49:02.520844Z","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":"2026-07-06T21:00:55.979837Z","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":"2026-08-07T11:49:02.632210Z","title":"Model context protocol (mcp): Landscape, security threats, and future research directions.arXiv preprint arXiv:2503.23278,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.01372","last_updated":"2025-06-09T09:01:24Z","snapshot_observed_at":"2026-08-09T03:01:37.763836Z","submitted_at":"2025-06-02T06:59:10Z","title":"AI Scientists Fail Without Strong Implementation Capability","version":2},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-08-07T11:49:02.632210Z"},"links":{"cited_paper":"/paper/2503.23278","citing_paper":"/paper/2506.01372"},"observation_digest":"sha256:4e1710f7344c03a25768c7ef968d7711ebe7b2a05db24ec20e435b19fb7378dd","observation_id":"9c3c27de-bd74-4666-b467-a0261a7fe174","resolution":{"observed_at":"2026-08-07T11:49:02.632210Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.14255","last_updated":"2024-10-27T04:02:32Z","snapshot_observed_at":"2026-07-06T19:35:48.603411Z","submitted_at":"2024-10-18T08:04:36Z","title":"Nova: An Iterative Planning and Search Approach to Enhance Novelty and Diversity of LLM Generated Ideas","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.14255","snapshot_observed_at":"2026-08-07T11:49:02.748535Z","title":"Nova: An iterative planning and search approach to enhance novelty and diversity of llm generated ideas.arXiv preprint arXiv:2410.14255,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.01372","last_updated":"2025-06-09T09:01:24Z","snapshot_observed_at":"2026-08-09T03:01:37.763836Z","submitted_at":"2025-06-02T06:59:10Z","title":"AI Scientists Fail Without Strong Implementation Capability","version":2},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-08-07T11:49:02.748535Z"},"links":{"cited_paper":"/paper/2410.14255","citing_paper":"/paper/2506.01372"},"observation_digest":"sha256:a4b7b613d93ae6e0e789250a4ba295a0d70d23aef012645e850d28121a70faaa","observation_id":"6ac99bae-9e1e-44f1-a113-6689bd9d5262","resolution":{"observed_at":"2026-08-07T11:49:02.748535Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2403.07974","last_updated":"2024-06-06T17:41:21Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-03-12T17:58:04Z","title":"LiveCodeBench: Holistic and Contamination Free Evaluation of Large Language Models for Code","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2403.07974","snapshot_observed_at":"2026-08-07T11:49:02.892900Z","title":"Naman Jain, King Han, Alex Gu, Wen-Ding Li, Fanjia Yan, Tianjun Zhang, Sida Wang, Armando Solar-Lezama, Koushik Sen, and Ion Stoica","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.01372","last_updated":"2025-06-09T09:01:24Z","snapshot_observed_at":"2026-08-09T03:01:37.763836Z","submitted_at":"2025-06-02T06:59:10Z","title":"AI Scientists Fail Without Strong Implementation Capability","version":2},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-08-07T11:49:02.892900Z"},"links":{"cited_paper":"/paper/2403.07974","citing_paper":"/paper/2506.01372"},"observation_digest":"sha256:ed2643f60d6ce8b9db887ddb009291330efbd5db42e933e5af2e00cd97421444","observation_id":"f6d4187c-14cb-48e7-9afa-2a8043bb77aa","resolution":{"observed_at":"2026-08-07T11:49:02.892900Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2503.22708","last_updated":"2025-03-20T22:37:17Z","snapshot_observed_at":"2026-08-08T17:38:00.873141Z","submitted_at":"2025-03-20T22:37:17Z","title":"CodeScientist: End-to-End Semi-Automated Scientific Discovery with Code-based Experimentation","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2503.22708","snapshot_observed_at":"2026-08-07T11:49:03.018962Z","title":"Codescientist: End-to-end semi-automated scientific discovery with code-based experimentation.arXiv preprint arXiv:2503.22708,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.01372","last_updated":"2025-06-09T09:01:24Z","snapshot_observed_at":"2026-08-09T03:01:37.763836Z","submitted_at":"2025-06-02T06:59:10Z","title":"AI Scientists Fail Without Strong Implementation Capability","version":2},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-07T11:49:03.018962Z"},"links":{"cited_paper":"/paper/2503.22708","citing_paper":"/paper/2506.01372"},"observation_digest":"sha256:76e6efbd2e53f911fa6c3f91be6d35b512ca257c9de8952da752961bedbbbc04","observation_id":"a76b139d-8395-4ad3-bb58-e36029c73cb7","resolution":{"observed_at":"2026-08-07T11:49:03.018962Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2502.13138","last_updated":"2025-02-18T18:57:21Z","snapshot_observed_at":"2026-08-05T07:03:00.655237Z","submitted_at":"2025-02-18T18:57:21Z","title":"AIDE: AI-Driven Exploration in the Space of Code","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2502.13138","snapshot_observed_at":"2026-08-07T11:49:03.119196Z","title":"Aide: Ai-driven exploration in the space of code.arXiv preprint arXiv:2502.13138,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.01372","last_updated":"2025-06-09T09:01:24Z","snapshot_observed_at":"2026-08-09T03:01:37.763836Z","submitted_at":"2025-06-02T06:59:10Z","title":"AI Scientists Fail Without Strong Implementation Capability","version":2},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-07T11:49:03.119196Z"},"links":{"cited_paper":"/paper/2502.13138","citing_paper":"/paper/2506.01372"},"observation_digest":"sha256:df76b95778108ea4a1abcc0eac87ac665bd59429d57599eb0ea23da69f3ffb62","observation_id":"c02ca024-d610-4280-b654-bec0e03fb7f3","resolution":{"observed_at":"2026-08-07T11:49:03.119196Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2505.06120","last_updated":"2025-05-09T15:21:44Z","snapshot_observed_at":"2026-08-08T19:35:51.229758Z","submitted_at":"2025-05-09T15:21:44Z","title":"LLMs Get Lost In Multi-Turn Conversation","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2505.06120","snapshot_observed_at":"2026-08-07T11:49:03.467915Z","title":"Llms get lost in multi-turn conversation","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.01372","last_updated":"2025-06-09T09:01:24Z","snapshot_observed_at":"2026-08-09T03:01:37.763836Z","submitted_at":"2025-06-02T06:59:10Z","title":"AI Scientists Fail Without Strong Implementation Capability","version":2},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-08-07T11:49:03.467915Z"},"links":{"cited_paper":"/paper/2505.06120","citing_paper":"/paper/2506.01372"},"observation_digest":"sha256:d8454c8c11a08c8819c101812ae32a0b141299f894be6d2d23cec6fea0d85975","observation_id":"204eeaaa-4a33-449e-8507-3885c6d0c685","resolution":{"observed_at":"2026-08-07T11:49:03.467915Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2411.15692","last_updated":"2025-03-05T10:54:30Z","snapshot_observed_at":"2026-07-06T19:56:04.259325Z","submitted_at":"2024-11-24T03:06:59Z","title":"DrugAgent: Automating AI-aided Drug Discovery Programming through LLM Multi-Agent Collaboration","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2411.15692","snapshot_observed_at":"2026-08-07T11:49:03.711750Z","title":"Drugagent: Au- tomating ai-aided drug discovery programming through llm multi-agent collaboration.arXiv preprint arXiv:2411.15692, 2024a","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.01372","last_updated":"2025-06-09T09:01:24Z","snapshot_observed_at":"2026-08-09T03:01:37.763836Z","submitted_at":"2025-06-02T06:59:10Z","title":"AI Scientists Fail Without Strong Implementation Capability","version":2},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-08-07T11:49:03.711750Z"},"links":{"cited_paper":"/paper/2411.15692","citing_paper":"/paper/2506.01372"},"observation_digest":"sha256:7a3a2a1a6df460db340cc2695455a8ebd6a924595725a9e065b9530f9ee29871","observation_id":"a2d5485d-3adc-4870-9c40-39e4f57dea87","resolution":{"observed_at":"2026-08-07T11:49:03.711750Z","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":"2026-07-06T19:52:11.774784Z","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":"2026-08-07T11:49:03.834636Z","title":"Aigs: Generating science from ai-powered automated falsification.arXiv preprint arXiv:2411.11910, 2024b","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.01372","last_updated":"2025-06-09T09:01:24Z","snapshot_observed_at":"2026-08-09T03:01:37.763836Z","submitted_at":"2025-06-02T06:59:10Z","title":"AI Scientists Fail Without Strong Implementation Capability","version":2},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-08-07T11:49:03.834636Z"},"links":{"cited_paper":"/paper/2411.11910","citing_paper":"/paper/2506.01372"},"observation_digest":"sha256:c232f01a887ab4c2e24381bc323840c0111191ce88832bdf715f1228d261caaa","observation_id":"6a05857c-d6ba-441d-967d-6954f3293163","resolution":{"observed_at":"2026-08-07T11:49:03.834636Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_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},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2408.06292","snapshot_observed_at":"2026-08-07T11:49:03.993632Z","title":"Amil Merchant, Simon Batzner, Samuel S Schoenholz, Muratahan Aykol, Gowoon Cheon, and Ekin Dogus Cubuk","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.01372","last_updated":"2025-06-09T09:01:24Z","snapshot_observed_at":"2026-08-09T03:01:37.763836Z","submitted_at":"2025-06-02T06:59:10Z","title":"AI Scientists Fail Without Strong Implementation Capability","version":2},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-08-07T11:49:03.993632Z"},"links":{"cited_paper":"/paper/2408.06292","citing_paper":"/paper/2506.01372"},"observation_digest":"sha256:a879d435b730be6bfd0b5b0570e015f96464cf4c1c32da8f865ca2c495e26a8b","observation_id":"235aaf50-4cd0-46de-b0e1-be7201172ac7","resolution":{"observed_at":"2026-08-07T11:49:03.993632Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2504.12976","last_updated":"2025-04-17T14:29:18Z","snapshot_observed_at":"2026-08-07T16:01:26.184746Z","submitted_at":"2025-04-17T14:29:18Z","title":"Sparks of Science: Hypothesis Generation Using Structured Paper Data","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2504.12976","snapshot_observed_at":"2026-08-07T11:49:04.355306Z","title":"Sparks of science: Hypothesis generation using structured paper data.arXiv preprint arXiv:2504.12976,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.01372","last_updated":"2025-06-09T09:01:24Z","snapshot_observed_at":"2026-08-09T03:01:37.763836Z","submitted_at":"2025-06-02T06:59:10Z","title":"AI Scientists Fail Without Strong Implementation Capability","version":2},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-07T11:49:04.355306Z"},"links":{"cited_paper":"/paper/2504.12976","citing_paper":"/paper/2506.01372"},"observation_digest":"sha256:bf2e7f14fa1105c9a5dee93e21342fc9ca8c721d33fbd067cc67ea915bd87581","observation_id":"aded90f8-1b0e-468e-93ab-0942d7935376","resolution":{"observed_at":"2026-08-07T11:49:04.355306Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2502.00964","last_updated":"2025-02-19T05:09:01Z","snapshot_observed_at":"2026-08-09T17:02:32.208398Z","submitted_at":"2025-02-03T00:04:49Z","title":"ML-Dev-Bench: Comparative Analysis of AI Agents on ML development workflows","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2502.00964","snapshot_observed_at":"2026-08-07T11:49:04.506588Z","title":"Mathis Pink, Qinyuan Wu, Vy Ai Vo, Javier Turek, Jianing Mu, Alexander Huth, and Mariya Toneva","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.01372","last_updated":"2025-06-09T09:01:24Z","snapshot_observed_at":"2026-08-09T03:01:37.763836Z","submitted_at":"2025-06-02T06:59:10Z","title":"AI Scientists Fail Without Strong Implementation Capability","version":2},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-08-07T11:49:04.506588Z"},"links":{"cited_paper":"/paper/2502.00964","citing_paper":"/paper/2506.01372"},"observation_digest":"sha256:66bb8c26948fc4df6278a990242e65dbec811e07897e693c09de8f8eb980c7d0","observation_id":"0beef106-8e32-460f-ac4f-fb8be80c23bf","resolution":{"observed_at":"2026-08-07T11:49:04.506588Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:49:04.638623Z","title":"Ideasynth: Iterative research idea development through evolving and composing idea facets with literature-grounded feedback","venue":null,"work_id":null,"year":2025},"citing_paper":{"arxiv_id":"2506.01372","last_updated":"2025-06-09T09:01:24Z","snapshot_observed_at":"2026-08-09T03:01:37.763836Z","submitted_at":"2025-06-02T06:59:10Z","title":"AI Scientists Fail Without Strong Implementation Capability","version":2},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-08-07T11:49:04.638623Z"},"links":{"citing_paper":"/paper/2506.01372"},"observation_digest":"sha256:2aade6835d44cb85f07e03f7700bb9da0e384cd28cd558cc70ba25d406de11f0","observation_id":"2361c1dc-27d8-4b59-8ae5-bf3f0db8e94a","resolution":{"observed_at":"2026-08-07T11:49:04.638623Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2503.19309","last_updated":"2025-03-25T03:14:53Z","snapshot_observed_at":"2026-08-07T16:39:29.622562Z","submitted_at":"2025-03-25T03:14:53Z","title":"Iterative Hypothesis Generation for Scientific Discovery with Monte Carlo Nash Equilibrium Self-Refining Trees","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2503.19309","snapshot_observed_at":"2026-08-07T11:49:04.767680Z","title":"Iterative hypothesis generation for scientific discovery with monte carlo nash equilibrium self-refining trees.arXiv preprint arXiv:2503.19309,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.01372","last_updated":"2025-06-09T09:01:24Z","snapshot_observed_at":"2026-08-09T03:01:37.763836Z","submitted_at":"2025-06-02T06:59:10Z","title":"AI Scientists Fail Without Strong Implementation Capability","version":2},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-08-07T11:49:04.767680Z"},"links":{"cited_paper":"/paper/2503.19309","citing_paper":"/paper/2506.01372"},"observation_digest":"sha256:833d575ce643d429c800003cd1d09b4fcae94d7f8b8f0768f197506390833936","observation_id":"6c18ebcd-7e77-4f2e-aa9a-5068916d1ea1","resolution":{"observed_at":"2026-08-07T11:49:04.767680Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_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},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2409.14634","snapshot_observed_at":"2026-08-07T11:49:04.917967Z","title":"Scideator: Human-llm scientific idea generation grounded in research-paper facet recombination.arXiv preprint arXiv:2409.14634,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.01372","last_updated":"2025-06-09T09:01:24Z","snapshot_observed_at":"2026-08-09T03:01:37.763836Z","submitted_at":"2025-06-02T06:59:10Z","title":"AI Scientists Fail Without Strong Implementation Capability","version":2},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-08-07T11:49:04.917967Z"},"links":{"cited_paper":"/paper/2409.14634","citing_paper":"/paper/2506.01372"},"observation_digest":"sha256:19082dae44622126c22ab5a510f8f4956592539caf4d7b049d3273f0c397c5f5","observation_id":"e6c7066e-a501-4827-89d2-c129711fd55f","resolution":{"observed_at":"2026-08-07T11:49:04.917967Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2503.23170","last_updated":"2025-03-29T17:58:52Z","snapshot_observed_at":"2026-08-07T16:28:17.630219Z","submitted_at":"2025-03-29T17:58:52Z","title":"AstroAgents: A Multi-Agent AI for Hypothesis Generation from Mass Spectrometry Data","version":1},"cited_work":{"arxiv_id":"2503.23170","doi":null,"metadata_source":"pith","pith_arxiv_id":"2503.23170","snapshot_observed_at":"2026-08-07T11:49:08.981159Z","title":"AstroAgents: A Multi-Agent AI for Hypothesis Generation from Mass Spectrometry Data","venue":"cs.AI","work_id":"a2bdaef8-1c46-4444-8a4b-4f9a0c105276","year":2025},"citing_paper":{"arxiv_id":"2506.01372","last_updated":"2025-06-09T09:01:24Z","snapshot_observed_at":"2026-08-09T03:01:37.763836Z","submitted_at":"2025-06-02T06:59:10Z","title":"AI Scientists Fail Without Strong Implementation Capability","version":2},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-08-07T11:49:05.074678Z"},"links":{"cited_paper":"/paper/2503.23170","citing_paper":"/paper/2506.01372"},"observation_digest":"sha256:e955544b9a7793048aacab17a50459d7fb4d4ed012efda1e45c15f6ab0fff969","observation_id":"39e3ba0f-4d41-4365-b62e-6c2cc684661d","resolution":{"observed_at":"2026-08-07T11:49:09.076092Z","resolver_source":"local_arxiv","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":"2504.20090","last_updated":"2025-05-21T18:26:09Z","snapshot_observed_at":"2026-08-07T15:59:06.099099Z","submitted_at":"2025-04-25T20:33:57Z","title":"Spark: A System for Scientifically Creative Idea Generation","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2504.20090","snapshot_observed_at":"2026-08-07T11:49:05.153250Z","title":"Spark: A system for scientifically creative idea generation.arXiv preprint arXiv:2504.20090,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.01372","last_updated":"2025-06-09T09:01:24Z","snapshot_observed_at":"2026-08-09T03:01:37.763836Z","submitted_at":"2025-06-02T06:59:10Z","title":"AI Scientists Fail Without Strong Implementation Capability","version":2},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-08-07T11:49:05.153250Z"},"links":{"cited_paper":"/paper/2504.20090","citing_paper":"/paper/2506.01372"},"observation_digest":"sha256:0681fdb277adfdce3636eb92c1bad531bde34fd6035dcfdc0e57f0e3ac4de61b","observation_id":"7d38d89a-c551-41ae-b75d-4196d32e43b5","resolution":{"observed_at":"2026-08-07T11:49:05.153250Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2501.04227","last_updated":"2025-06-17T16:19:14Z","snapshot_observed_at":"2026-08-03T03:40:06.947021Z","submitted_at":"2025-01-08T01:58:42Z","title":"Agent Laboratory: Using LLM Agents as Research Assistants","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2501.04227","snapshot_observed_at":"2026-08-07T11:49:05.207479Z","title":"Agent laboratory: Using llm agents as research assistants.arXiv preprint arXiv:2501.04227,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.01372","last_updated":"2025-06-09T09:01:24Z","snapshot_observed_at":"2026-08-09T03:01:37.763836Z","submitted_at":"2025-06-02T06:59:10Z","title":"AI Scientists Fail Without Strong Implementation Capability","version":2},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-08-07T11:49:05.207479Z"},"links":{"cited_paper":"/paper/2501.04227","citing_paper":"/paper/2506.01372"},"observation_digest":"sha256:5fa444542e159775c81a232d333667ee8d817b1ed7eab9f5417d59ec8942e0a1","observation_id":"cc5ffc26-7b64-4ee9-a7e9-e83c1cd9c747","resolution":{"observed_at":"2026-08-07T11:49:05.207479Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:49:05.244211Z","title":"Paper2code: Automating code generation from scientific papers in machine learning.arXiv preprint arXiv:2504.17192,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.01372","last_updated":"2025-06-09T09:01:24Z","snapshot_observed_at":"2026-08-09T03:01:37.763836Z","submitted_at":"2025-06-02T06:59:10Z","title":"AI Scientists Fail Without Strong Implementation Capability","version":2},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-08-07T11:49:05.244211Z"},"links":{"citing_paper":"/paper/2506.01372"},"observation_digest":"sha256:8ab52eb108c122202584a0fab315902592f20965fa2d0a75f7bb1f86b7486f99","observation_id":"30edacd1-f051-4d43-991f-dc5313864317","resolution":{"observed_at":"2026-08-07T11:49:05.244211Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2407.00132","last_updated":"2025-01-23T11:22:20Z","snapshot_observed_at":"2026-07-06T18:38:42.333605Z","submitted_at":"2024-06-28T08:45:02Z","title":"ShortcutsBench: A Large-Scale Real-world Benchmark for API-based Agents","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2407.00132","snapshot_observed_at":"2026-08-07T11:49:05.401684Z","title":"Chenglei Si, Diyi Yang, and Tatsunori Hashimoto","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.01372","last_updated":"2025-06-09T09:01:24Z","snapshot_observed_at":"2026-08-09T03:01:37.763836Z","submitted_at":"2025-06-02T06:59:10Z","title":"AI Scientists Fail Without Strong Implementation Capability","version":2},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-08-07T11:49:05.401684Z"},"links":{"cited_paper":"/paper/2407.00132","citing_paper":"/paper/2506.01372"},"observation_digest":"sha256:6fb0bc718e38a95ff4922b9e5223c9b1ae4fcc297a7e9551e61aaa634ef73b4e","observation_id":"73dccdd8-c7f9-4942-a0aa-e64bb379a31b","resolution":{"observed_at":"2026-08-07T11:49:05.401684Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:49:12.147693Z","title":"Canllmsgeneratenovelresearchideas? Alarge-scalehuman study with 100+ NLP researchers","venue":null,"work_id":"46ba6f78-25cd-4f98-879f-f213d6cacd62","year":2025},"citing_paper":{"arxiv_id":"2506.01372","last_updated":"2025-06-09T09:01:24Z","snapshot_observed_at":"2026-08-09T03:01:37.763836Z","submitted_at":"2025-06-02T06:59:10Z","title":"AI Scientists Fail Without Strong Implementation Capability","version":2},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-08-07T11:49:05.535880Z"},"links":{"citing_paper":"/paper/2506.01372"},"observation_digest":"sha256:29e88e9bb3292618e52657199a1a4fc3d68cf3b823bd19b2bb2d8edff9a386ef","observation_id":"45f7760b-c717-4a88-9d42-87d77cc67b1e","resolution":{"observed_at":"2026-08-07T11:49:12.287112Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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":"2409.11363","last_updated":"2026-06-22T22:36:12Z","snapshot_observed_at":"2026-08-07T20:31:37.591767Z","submitted_at":"2024-09-17T17:13:19Z","title":"CORE-Bench: Fostering the Credibility of Published Research Through a Computational Reproducibility Agent Benchmark","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2409.11363","snapshot_observed_at":"2026-08-07T11:49:05.670557Z","title":"Zachary S Siegel, Sayash Kapoor, Nitya Nagdir, Benedikt Stroebl, and Arvind Narayanan","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.01372","last_updated":"2025-06-09T09:01:24Z","snapshot_observed_at":"2026-08-09T03:01:37.763836Z","submitted_at":"2025-06-02T06:59:10Z","title":"AI Scientists Fail Without Strong Implementation Capability","version":2},"reference_index":40,"source":"pdf_text","source_observed_at":"2026-08-07T11:49:05.670557Z"},"links":{"cited_paper":"/paper/2409.11363","citing_paper":"/paper/2506.01372"},"observation_digest":"sha256:440d7b7ac043c39551fc1ef7c4556b6950fbf0c6dfe2db6cd2d77d515d2bc16f","observation_id":"02fe6701-6a4d-4a7d-9d10-30c697994b52","resolution":{"observed_at":"2026-08-07T11:49:05.670557Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2504.01848","last_updated":"2025-04-07T12:15:49Z","snapshot_observed_at":"2026-07-06T21:03:06.857885Z","submitted_at":"2025-04-02T15:55:24Z","title":"PaperBench: Evaluating AI's Ability to Replicate AI Research","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2504.01848","snapshot_observed_at":"2026-08-07T11:49:05.813810Z","title":"Paperbench: Evaluating ai’s ability to replicate ai research.arXiv preprint arXiv:2504.01848,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.01372","last_updated":"2025-06-09T09:01:24Z","snapshot_observed_at":"2026-08-09T03:01:37.763836Z","submitted_at":"2025-06-02T06:59:10Z","title":"AI Scientists Fail Without Strong Implementation Capability","version":2},"reference_index":41,"source":"pdf_text","source_observed_at":"2026-08-07T11:49:05.813810Z"},"links":{"cited_paper":"/paper/2504.01848","citing_paper":"/paper/2506.01372"},"observation_digest":"sha256:bdd7cffcbf2f8c8076162220b1445a041bd701f2be65a3369c492cb5c1c4edfd","observation_id":"697ba589-c9bd-428e-9c24-33fdf2a7200f","resolution":{"observed_at":"2026-08-07T11:49:05.813810Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2505.04588","last_updated":"2026-05-19T11:51:42Z","snapshot_observed_at":"2026-08-04T18:36:41.979541Z","submitted_at":"2025-05-07T17:30:22Z","title":"ZeroSearch: Incentivize the Search Capability of LLMs without Searching","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2505.04588","snapshot_observed_at":"2026-08-07T11:49:06.037989Z","title":"Zerosearch: Incentivize the search capability of llms without searching.arXiv preprint arXiv:2505.04588,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.01372","last_updated":"2025-06-09T09:01:24Z","snapshot_observed_at":"2026-08-09T03:01:37.763836Z","submitted_at":"2025-06-02T06:59:10Z","title":"AI Scientists Fail Without Strong Implementation Capability","version":2},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-08-07T11:49:06.037989Z"},"links":{"cited_paper":"/paper/2505.04588","citing_paper":"/paper/2506.01372"},"observation_digest":"sha256:850ea12b27dd6e2cd29c6d9488e1c70080797e7c449543baec1bc54eda68a96a","observation_id":"de0a2467-344b-4148-9fc7-a3d9826f11f3","resolution":{"observed_at":"2026-08-07T11:49:06.037989Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.23166","last_updated":"2025-02-17T08:59:45Z","snapshot_observed_at":"2026-08-08T00:00:08.825747Z","submitted_at":"2024-10-30T16:18:22Z","title":"SciPIP: An LLM-based Scientific Paper Idea Proposer","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.23166","snapshot_observed_at":"2026-08-07T11:49:06.160799Z","title":"SciMON: Scientific inspiration machines optimized for novelty","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.01372","last_updated":"2025-06-09T09:01:24Z","snapshot_observed_at":"2026-08-09T03:01:37.763836Z","submitted_at":"2025-06-02T06:59:10Z","title":"AI Scientists Fail Without Strong Implementation Capability","version":2},"reference_index":44,"source":"pdf_text","source_observed_at":"2026-08-07T11:49:06.160799Z"},"links":{"cited_paper":"/paper/2410.23166","citing_paper":"/paper/2506.01372"},"observation_digest":"sha256:f51a14d4ad75b4381448dd331d1b4583296cf6011a5b652c7f6a48225877edcb","observation_id":"84be6792-5dfa-49f8-92da-dcfd78801cc6","resolution":{"observed_at":"2026-08-07T11:49:06.160799Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:49:06.281808Z","title":"Large language models are better reasoners with self-verification","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2506.01372","last_updated":"2025-06-09T09:01:24Z","snapshot_observed_at":"2026-08-09T03:01:37.763836Z","submitted_at":"2025-06-02T06:59:10Z","title":"AI Scientists Fail Without Strong Implementation Capability","version":2},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-08-07T11:49:06.281808Z"},"links":{"citing_paper":"/paper/2506.01372"},"observation_digest":"sha256:9ccbaeae1335a632a50bf9da306a8ddad839ed8c3aff32c16ffa8095c1a4a5e7","observation_id":"43e630c0-337e-430f-94d1-27ccad2cdf6e","resolution":{"observed_at":"2026-08-07T11:49:06.281808Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2503.04723","last_updated":"2025-03-07T03:14:02Z","snapshot_observed_at":"2026-08-07T17:23:48.104491Z","submitted_at":"2025-03-06T18:59:37Z","title":"Shifting Long-Context LLMs Research from Input to Output","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2503.04723","snapshot_observed_at":"2026-08-07T11:49:06.406833Z","title":"Yuhao Wu, Yushi Bai, Zhiqing Hu, Shangqing Tu, Ming Shan Hee, Juanzi Li, and Roy Ka-Wei Lee","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.01372","last_updated":"2025-06-09T09:01:24Z","snapshot_observed_at":"2026-08-09T03:01:37.763836Z","submitted_at":"2025-06-02T06:59:10Z","title":"AI Scientists Fail Without Strong Implementation Capability","version":2},"reference_index":46,"source":"pdf_text","source_observed_at":"2026-08-07T11:49:06.406833Z"},"links":{"cited_paper":"/paper/2503.04723","citing_paper":"/paper/2506.01372"},"observation_digest":"sha256:bf0678ec7f98141122e65c0464986c8490bbdb253a1a4ec8fe922afe480df91c","observation_id":"b3a60b3c-a999-42e4-8cf4-12660257330c","resolution":{"observed_at":"2026-08-07T11:49:06.406833Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2411.02382","last_updated":"2024-11-04T18:50:00Z","snapshot_observed_at":"2026-07-06T19:45:00.034364Z","submitted_at":"2024-11-04T18:50:00Z","title":"Improving Scientific Hypothesis Generation with Knowledge Grounded Large Language Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2411.02382","snapshot_observed_at":"2026-08-07T11:49:06.537534Z","title":"Guangzhi Xiong, Eric Xie, Amir Hassan Shariatmadari, Sikun Guo, Stefan Bekiranov, and Aidong Zhang","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.01372","last_updated":"2025-06-09T09:01:24Z","snapshot_observed_at":"2026-08-09T03:01:37.763836Z","submitted_at":"2025-06-02T06:59:10Z","title":"AI Scientists Fail Without Strong Implementation Capability","version":2},"reference_index":47,"source":"pdf_text","source_observed_at":"2026-08-07T11:49:06.537534Z"},"links":{"cited_paper":"/paper/2411.02382","citing_paper":"/paper/2506.01372"},"observation_digest":"sha256:274ca6f46577f715a713d61d610627170bc91a9c37861ca306f866ae4c23567c","observation_id":"8fdc8173-864d-447b-9033-9030ba33c6ee","resolution":{"observed_at":"2026-08-07T11:49:06.537534Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2504.08066","last_updated":"2025-04-10T18:44:41Z","snapshot_observed_at":"2026-08-01T14:58:15.255937Z","submitted_at":"2025-04-10T18:44:41Z","title":"The AI Scientist-v2: Workshop-Level Automated Scientific Discovery via Agentic Tree Search","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2504.08066","snapshot_observed_at":"2026-08-07T11:49:06.629089Z","title":"The ai scientist-v2: Workshop-level automated scientific discovery via agentic tree search.arXiv preprint arXiv:2504.08066,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.01372","last_updated":"2025-06-09T09:01:24Z","snapshot_observed_at":"2026-08-09T03:01:37.763836Z","submitted_at":"2025-06-02T06:59:10Z","title":"AI Scientists Fail Without Strong Implementation Capability","version":2},"reference_index":48,"source":"pdf_text","source_observed_at":"2026-08-07T11:49:06.629089Z"},"links":{"cited_paper":"/paper/2504.08066","citing_paper":"/paper/2506.01372"},"observation_digest":"sha256:c9dec9703b6a34fb61545dcc157b94e072ab38a7ce062b6217fbbbf420d80bb4","observation_id":"3749524d-2ac7-4278-af41-25adaf01aefa","resolution":{"observed_at":"2026-08-07T11:49:06.629089Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2505.09388","last_updated":"2025-05-14T13:41:34Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-05-14T13:41:34Z","title":"Qwen3 Technical Report","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2505.09388","snapshot_observed_at":"2026-08-07T11:49:06.712106Z","title":"Qwen3 technical report.arXiv preprint arXiv:2505.09388, 2025a","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.01372","last_updated":"2025-06-09T09:01:24Z","snapshot_observed_at":"2026-08-09T03:01:37.763836Z","submitted_at":"2025-06-02T06:59:10Z","title":"AI Scientists Fail Without Strong Implementation Capability","version":2},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-08-07T11:49:06.712106Z"},"links":{"cited_paper":"/paper/2505.09388","citing_paper":"/paper/2506.01372"},"observation_digest":"sha256:2061d809fa0276138ff4f1f1e5ed774dc559cd67d45f717350086accc4d5fa01","observation_id":"2e2b4c57-17d5-4d04-b0f0-534c632e87cc","resolution":{"observed_at":"2026-08-07T11:49:06.712106Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2412.17767","last_updated":"2025-06-06T04:39:34Z","snapshot_observed_at":"2026-07-06T20:12:18.144353Z","submitted_at":"2024-12-23T18:26:53Z","title":"ResearchTown: Simulator of Human Research Community","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2412.17767","snapshot_observed_at":"2026-08-07T11:49:06.773231Z","title":"MOOSE-chem: Large language models for rediscovering unseen chemistry scientific hypotheses","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.01372","last_updated":"2025-06-09T09:01:24Z","snapshot_observed_at":"2026-08-09T03:01:37.763836Z","submitted_at":"2025-06-02T06:59:10Z","title":"AI Scientists Fail Without Strong Implementation Capability","version":2},"reference_index":50,"source":"pdf_text","source_observed_at":"2026-08-07T11:49:06.773231Z"},"links":{"cited_paper":"/paper/2412.17767","citing_paper":"/paper/2506.01372"},"observation_digest":"sha256:c638bd6f03b12e9d202e1266e24dfc588e8b3509da060522c1e26b6f2e71e34d","observation_id":"ac39e507-a84f-499d-85d7-57c8fcc4520f","resolution":{"observed_at":"2026-08-07T11:49:06.773231Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2501.03916","last_updated":"2025-04-09T16:27:02Z","snapshot_observed_at":"2026-07-06T20:17:43.203959Z","submitted_at":"2025-01-07T16:31:10Z","title":"Dolphin: Moving Towards Closed-loop Auto-research through Thinking, Practice, and Feedback","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2501.03916","snapshot_observed_at":"2026-08-07T11:49:06.874611Z","title":"Dolphin: Closed-loop open-ended auto-research through thinking, practice, and feedback.arXiv preprint arXiv:2501.03916,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.01372","last_updated":"2025-06-09T09:01:24Z","snapshot_observed_at":"2026-08-09T03:01:37.763836Z","submitted_at":"2025-06-02T06:59:10Z","title":"AI Scientists Fail Without Strong Implementation Capability","version":2},"reference_index":51,"source":"pdf_text","source_observed_at":"2026-08-07T11:49:06.874611Z"},"links":{"cited_paper":"/paper/2501.03916","citing_paper":"/paper/2506.01372"},"observation_digest":"sha256:d6e48a88c69271eb1e13bb08cc1e5afb87d7e207b5b3bc4db78bfede74999c3c","observation_id":"bd66b695-43eb-4d03-a77a-27df4917229c","resolution":{"observed_at":"2026-08-07T11:49:06.874611Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2503.24235","last_updated":"2025-05-04T15:48:08Z","snapshot_observed_at":"2026-08-07T23:06:45.603790Z","submitted_at":"2025-03-31T15:46:15Z","title":"A Survey on Test-Time Scaling in Large Language Models: What, How, Where, and How Well?","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2503.24235","snapshot_observed_at":"2026-08-07T11:49:06.967707Z","title":"A survey on test-time scaling in large language models: What, how, where, and how well?arXiv preprint arXiv:2503.24235,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.01372","last_updated":"2025-06-09T09:01:24Z","snapshot_observed_at":"2026-08-09T03:01:37.763836Z","submitted_at":"2025-06-02T06:59:10Z","title":"AI Scientists Fail Without Strong Implementation Capability","version":2},"reference_index":52,"source":"pdf_text","source_observed_at":"2026-08-07T11:49:06.967707Z"},"links":{"cited_paper":"/paper/2503.24235","citing_paper":"/paper/2506.01372"},"observation_digest":"sha256:0c7fe2cd85baa13687f2ad2ffa53bcdaa75f34c7cba4ace5df041b9a71eaeb53","observation_id":"c0e1b13b-fb6f-4693-bfb9-df451bed8998","resolution":{"observed_at":"2026-08-07T11:49:06.967707Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2408.06941","last_updated":"2024-10-28T07:51:29Z","snapshot_observed_at":"2026-08-04T10:05:34.178876Z","submitted_at":"2024-08-13T14:59:44Z","title":"OpenResearcher: Unleashing AI for Accelerated Scientific Research","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2408.06941","snapshot_observed_at":"2026-08-07T11:49:07.021150Z","title":"Openresearcher: Unleashing ai for accelerated scientific research.arXiv preprint arXiv:2408.06941,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.01372","last_updated":"2025-06-09T09:01:24Z","snapshot_observed_at":"2026-08-09T03:01:37.763836Z","submitted_at":"2025-06-02T06:59:10Z","title":"AI Scientists Fail Without Strong Implementation Capability","version":2},"reference_index":53,"source":"pdf_text","source_observed_at":"2026-08-07T11:49:07.021150Z"},"links":{"cited_paper":"/paper/2408.06941","citing_paper":"/paper/2506.01372"},"observation_digest":"sha256:c98a367fe74208bfa40702e536946a43d921bc9435e5412618a5bd7cba5ecd97","observation_id":"ac38bdae-467d-4f26-842e-a8c00a2581cc","resolution":{"observed_at":"2026-08-07T11:49:07.021150Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2503.08569","last_updated":"2025-03-11T15:59:43Z","snapshot_observed_at":"2026-08-07T17:12:32.675735Z","submitted_at":"2025-03-11T15:59:43Z","title":"DeepReview: Improving LLM-based Paper Review with Human-like Deep Thinking Process","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2503.08569","snapshot_observed_at":"2026-08-07T11:49:07.108809Z","title":"Deepreview: Improving llm-based paper review with human-like deep thinking process.arXiv preprint arXiv:2503.08569,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.01372","last_updated":"2025-06-09T09:01:24Z","snapshot_observed_at":"2026-08-09T03:01:37.763836Z","submitted_at":"2025-06-02T06:59:10Z","title":"AI Scientists Fail Without Strong Implementation Capability","version":2},"reference_index":54,"source":"pdf_text","source_observed_at":"2026-08-07T11:49:07.108809Z"},"links":{"cited_paper":"/paper/2503.08569","citing_paper":"/paper/2506.01372"},"observation_digest":"sha256:52e8f02f831da536cc971ef625450ee90d370c0525975572a10e554edede725c","observation_id":"65160443-072e-4bf0-b947-7d4a503fc407","resolution":{"observed_at":"2026-08-07T11:49:07.108809Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:49:11.929406Z","title":null,"venue":null,"work_id":"edef2d3f-95c6-4a3d-99cd-8601991fd152","year":2025},"citing_paper":{"arxiv_id":"2506.01372","last_updated":"2025-06-09T09:01:24Z","snapshot_observed_at":"2026-08-09T03:01:37.763836Z","submitted_at":"2025-06-02T06:59:10Z","title":"AI Scientists Fail Without Strong Implementation Capability","version":2},"reference_index":55,"source":"pdf_text","source_observed_at":"2026-08-07T11:49:07.196636Z"},"links":{"citing_paper":"/paper/2506.01372"},"observation_digest":"sha256:62cb193869e9f836cc4d7a6693668a6ff439e4dc6d5ebd30f79fcc937d5e4847","observation_id":"22ce0db0-4cfd-4eba-9b78-1bf14c45e807","resolution":{"observed_at":"2026-08-07T11:49:12.017902Z","resolver_source":"raw_fallback","status":"unresolved"},"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":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:49:11.713036Z","title":"20 AI Scientists Fail Without Strong Implementation Capability","venue":null,"work_id":"fd93f466-374d-4571-9ac1-e30a923a9f80","year":2024},"citing_paper":{"arxiv_id":"2506.01372","last_updated":"2025-06-09T09:01:24Z","snapshot_observed_at":"2026-08-09T03:01:37.763836Z","submitted_at":"2025-06-02T06:59:10Z","title":"AI Scientists Fail Without Strong Implementation Capability","version":2},"reference_index":56,"source":"pdf_text","source_observed_at":"2026-08-07T11:49:07.292111Z"},"links":{"citing_paper":"/paper/2506.01372"},"observation_digest":"sha256:51019cbe81d93ee3b3e0673c74f309a54d90c8c24d9a385b79537b5ca340c97c","observation_id":"9f75f9e0-8ad2-49d0-9c37-ae48a51465cb","resolution":{"observed_at":"2026-08-07T11:49:11.816501Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:49:11.443205Z","title":null,"venue":null,"work_id":"e7f7fd76-3eaa-4486-ada9-f7c853321868","year":2024},"citing_paper":{"arxiv_id":"2506.01372","last_updated":"2025-06-09T09:01:24Z","snapshot_observed_at":"2026-08-09T03:01:37.763836Z","submitted_at":"2025-06-02T06:59:10Z","title":"AI Scientists Fail Without Strong Implementation Capability","version":2},"reference_index":57,"source":"pdf_text","source_observed_at":"2026-08-07T11:49:07.393120Z"},"links":{"citing_paper":"/paper/2506.01372"},"observation_digest":"sha256:850e94deac3dd5fe0a7c9f51a775fbdb109ea5d66bf716165d72962af141b503","observation_id":"da08517b-7ead-4848-8887-6e2a8692ecee","resolution":{"observed_at":"2026-08-07T11:49:11.589600Z","resolver_source":"raw_fallback","status":"unresolved"},"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":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:49:11.215742Z","title":null,"venue":null,"work_id":"a4e3b462-87c7-4c30-8ef7-999a80e400f1","year":2024},"citing_paper":{"arxiv_id":"2506.01372","last_updated":"2025-06-09T09:01:24Z","snapshot_observed_at":"2026-08-09T03:01:37.763836Z","submitted_at":"2025-06-02T06:59:10Z","title":"AI Scientists Fail Without Strong Implementation Capability","version":2},"reference_index":58,"source":"pdf_text","source_observed_at":"2026-08-07T11:49:07.495776Z"},"links":{"citing_paper":"/paper/2506.01372"},"observation_digest":"sha256:33723958898001c3fa170437305aa6146225e7bce64ac0eabaebe49b18cbd0fb","observation_id":"915f0bc9-9492-486b-b8a0-8002cdd1da20","resolution":{"observed_at":"2026-08-07T11:49:11.299542Z","resolver_source":"raw_fallback","status":"unresolved"},"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":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:49:11.015715Z","title":null,"venue":null,"work_id":"7b6ca21c-1616-4dec-bf49-2e8952180b39","year":2025},"citing_paper":{"arxiv_id":"2506.01372","last_updated":"2025-06-09T09:01:24Z","snapshot_observed_at":"2026-08-09T03:01:37.763836Z","submitted_at":"2025-06-02T06:59:10Z","title":"AI Scientists Fail Without Strong Implementation Capability","version":2},"reference_index":59,"source":"pdf_text","source_observed_at":"2026-08-07T11:49:07.630519Z"},"links":{"citing_paper":"/paper/2506.01372"},"observation_digest":"sha256:b30522ccaf9892f6d9f8ef5a4c20d708999a36bd7a1416fd5124ece0fc402602","observation_id":"de53a12d-9fb8-474d-accd-d93fc7eb84f1","resolution":{"observed_at":"2026-08-07T11:49:11.107790Z","resolver_source":"raw_fallback","status":"unresolved"},"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":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:49:10.706783Z","title":null,"venue":null,"work_id":"c44e79f2-d4e3-4e8f-9539-48b1470bbace","year":2025},"citing_paper":{"arxiv_id":"2506.01372","last_updated":"2025-06-09T09:01:24Z","snapshot_observed_at":"2026-08-09T03:01:37.763836Z","submitted_at":"2025-06-02T06:59:10Z","title":"AI Scientists Fail Without Strong Implementation Capability","version":2},"reference_index":60,"source":"pdf_text","source_observed_at":"2026-08-07T11:49:07.747320Z"},"links":{"citing_paper":"/paper/2506.01372"},"observation_digest":"sha256:bbdc35ee51d5144f4e3299becdd366ed4f9c4fc9f01c85b1bdc3a9d867cf5fe8","observation_id":"fcf12ab1-8867-44de-bf73-2ff2ea178a2e","resolution":{"observed_at":"2026-08-07T11:49:10.828847Z","resolver_source":"raw_fallback","status":"unresolved"},"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":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:49:10.392887Z","title":null,"venue":null,"work_id":"0df5c07b-a8b1-4138-86d1-d5bcb86bc794","year":2024},"citing_paper":{"arxiv_id":"2506.01372","last_updated":"2025-06-09T09:01:24Z","snapshot_observed_at":"2026-08-09T03:01:37.763836Z","submitted_at":"2025-06-02T06:59:10Z","title":"AI Scientists Fail Without Strong Implementation Capability","version":2},"reference_index":61,"source":"pdf_text","source_observed_at":"2026-08-07T11:49:07.952347Z"},"links":{"citing_paper":"/paper/2506.01372"},"observation_digest":"sha256:05280b670ef521d1a1f449022d689074d84b97527ae7819ff7c6526f3b2679bc","observation_id":"e9a5207f-ab4c-4ab9-bb35-e21f6bb3a22d","resolution":{"observed_at":"2026-08-07T11:49:10.568651Z","resolver_source":"raw_fallback","status":"unresolved"},"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":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:49:10.165321Z","title":null,"venue":null,"work_id":"dfe23eb9-4d0e-42d5-8395-cc19f109ccb0","year":2025},"citing_paper":{"arxiv_id":"2506.01372","last_updated":"2025-06-09T09:01:24Z","snapshot_observed_at":"2026-08-09T03:01:37.763836Z","submitted_at":"2025-06-02T06:59:10Z","title":"AI Scientists Fail Without Strong Implementation Capability","version":2},"reference_index":62,"source":"pdf_text","source_observed_at":"2026-08-07T11:49:08.144957Z"},"links":{"citing_paper":"/paper/2506.01372"},"observation_digest":"sha256:3c5f77b284b63b2521fd503743caf843a64ea043308024d221473eba01940c56","observation_id":"7891ea88-2462-4c41-9c95-90195d0ccbbb","resolution":{"observed_at":"2026-08-07T11:49:10.280713Z","resolver_source":"raw_fallback","status":"unresolved"},"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":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:49:09.909093Z","title":null,"venue":null,"work_id":"8dd70fae-cef9-434c-b447-a4e8f69ac611","year":2025},"citing_paper":{"arxiv_id":"2506.01372","last_updated":"2025-06-09T09:01:24Z","snapshot_observed_at":"2026-08-09T03:01:37.763836Z","submitted_at":"2025-06-02T06:59:10Z","title":"AI Scientists Fail Without Strong Implementation Capability","version":2},"reference_index":63,"source":"pdf_text","source_observed_at":"2026-08-07T11:49:08.278926Z"},"links":{"citing_paper":"/paper/2506.01372"},"observation_digest":"sha256:e921c5a69e4aff90ccb4985e4d360ebdb18bcaa4f5eec15cf35ce4f1fb5404c2","observation_id":"d31021fc-58fb-40a7-bf35-a0eb1c798360","resolution":{"observed_at":"2026-08-07T11:49:10.030667Z","resolver_source":"raw_fallback","status":"unresolved"},"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":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:49:09.652848Z","title":null,"venue":null,"work_id":"7a5a23b7-bf96-4c12-8cca-0526c3dcda6e","year":2025},"citing_paper":{"arxiv_id":"2506.01372","last_updated":"2025-06-09T09:01:24Z","snapshot_observed_at":"2026-08-09T03:01:37.763836Z","submitted_at":"2025-06-02T06:59:10Z","title":"AI Scientists Fail Without Strong Implementation Capability","version":2},"reference_index":64,"source":"pdf_text","source_observed_at":"2026-08-07T11:49:08.400971Z"},"links":{"citing_paper":"/paper/2506.01372"},"observation_digest":"sha256:12ed648ee2fda4c53c3fa5332ef6de095011af4876f253d255246087a9623da5","observation_id":"a58418a2-43df-4c82-8413-ba25425592fb","resolution":{"observed_at":"2026-08-07T11:49:09.735966Z","resolver_source":"raw_fallback","status":"unresolved"},"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":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:49:09.446638Z","title":"Regarding the statistics for the papers We have conducted a comprehensive search on arXiv to gather relevant publications in the AI Scientist field","venue":null,"work_id":"02303912-f599-445b-8dc5-f1dcd7a16ce8","year":2024},"citing_paper":{"arxiv_id":"2506.01372","last_updated":"2025-06-09T09:01:24Z","snapshot_observed_at":"2026-08-09T03:01:37.763836Z","submitted_at":"2025-06-02T06:59:10Z","title":"AI Scientists Fail Without Strong Implementation Capability","version":2},"reference_index":65,"source":"pdf_text","source_observed_at":"2026-08-07T11:49:08.589917Z"},"links":{"citing_paper":"/paper/2506.01372"},"observation_digest":"sha256:1a8546879d8b6f6cafba8cbd6b002981115baea5f131437051fba01e7e7bce77","observation_id":"25f635d1-381d-415d-9193-43ec5624fd91","resolution":{"observed_at":"2026-08-07T11:49:09.569047Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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":"2410.13185","last_updated":"2024-10-30T09:17:59Z","snapshot_observed_at":"2026-08-07T12:16:59.609877Z","submitted_at":"2024-10-17T03:26:37Z","title":"Chain of Ideas: Revolutionizing Research Via Novel Idea Development with LLM Agents","version":5},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.13185","snapshot_observed_at":"2026-08-07T11:49:03.588515Z","title":"Chain of ideas: Revolutionizing research via novel idea development with llm agents.arXiv preprint arXiv:2410.13185, 2024a","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.01372","last_updated":"2025-06-09T09:01:24Z","snapshot_observed_at":"2026-08-09T03:01:37.763836Z","submitted_at":"2025-06-02T06:59:10Z","title":"AI Scientists Fail Without Strong Implementation Capability","version":2},"reference_index":1987,"source":"pdf_text","source_observed_at":"2026-08-07T11:49:03.588515Z"},"links":{"cited_paper":"/paper/2410.13185","citing_paper":"/paper/2506.01372"},"observation_digest":"sha256:52cfb630d0d9c7673b44ed466468438b86f7648dc42e35dcc3f20e03ce58b3bc","observation_id":"31bcb75f-f68b-4ef5-a051-1338c4ea2a27","resolution":{"observed_at":"2026-08-07T11:49:03.588515Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2502.16069","last_updated":"2025-02-26T02:33:28Z","snapshot_observed_at":"2026-08-07T17:57:03.784569Z","submitted_at":"2025-02-22T03:58:19Z","title":"Curie: Toward Rigorous and Automated Scientific Experimentation with AI Agents","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2502.16069","snapshot_observed_at":"2026-08-07T11:49:03.336587Z","title":"Curie: Toward rigorous and automated scientific experimentation with ai agents.arXiv preprint arXiv:2502.16069,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.01372","last_updated":"2025-06-09T09:01:24Z","snapshot_observed_at":"2026-08-09T03:01:37.763836Z","submitted_at":"2025-06-02T06:59:10Z","title":"AI Scientists Fail Without Strong Implementation Capability","version":2},"reference_index":2009,"source":"pdf_text","source_observed_at":"2026-08-07T11:49:03.336587Z"},"links":{"cited_paper":"/paper/2502.16069","citing_paper":"/paper/2506.01372"},"observation_digest":"sha256:1d1ac7dc71656b0ce109284f21c1e90e137f2783cf3e04e4b0c85e37434da4be","observation_id":"50602bd2-cd08-49dd-99ad-4b24cadfc3b9","resolution":{"observed_at":"2026-08-07T11:49:03.336587Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2501.19393","last_updated":"2025-03-01T06:07:39Z","snapshot_observed_at":"2026-07-06T20:29:11.710285Z","submitted_at":"2025-01-31T18:48:08Z","title":"s1: Simple test-time scaling","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2501.19393","snapshot_observed_at":"2026-08-07T11:49:04.160309Z","title":"s1: Simple test-time scaling.arXiv preprint arXiv:2501.19393,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.01372","last_updated":"2025-06-09T09:01:24Z","snapshot_observed_at":"2026-08-09T03:01:37.763836Z","submitted_at":"2025-06-02T06:59:10Z","title":"AI Scientists Fail Without Strong Implementation Capability","version":2},"reference_index":2013,"source":"pdf_text","source_observed_at":"2026-08-07T11:49:04.160309Z"},"links":{"cited_paper":"/paper/2501.19393","citing_paper":"/paper/2506.01372"},"observation_digest":"sha256:a03ce22c7b32585cd1e9e20062197e62853cc318a8558dc2c5aab9e5c7e30494","observation_id":"8a0a26d8-9c2c-4f9e-96fc-38ad2251bbf6","resolution":{"observed_at":"2026-08-07T11:49:04.160309Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2410.09403","last_updated":"2025-05-27T03:47:05Z","snapshot_observed_at":"2026-08-04T20:05:10.828580Z","submitted_at":"2024-10-12T07:16:22Z","title":"Many Heads Are Better Than One: Improved Scientific Idea Generation by A LLM-Based Multi-Agent System","version":4},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.09403","snapshot_observed_at":"2026-08-07T11:49:05.903065Z","title":"Two heads are better than one: A multi-agent system has the potential to improve scientific idea generation.arXiv preprint arXiv:2410.09403,","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.01372","last_updated":"2025-06-09T09:01:24Z","snapshot_observed_at":"2026-08-09T03:01:37.763836Z","submitted_at":"2025-06-02T06:59:10Z","title":"AI Scientists Fail Without Strong Implementation Capability","version":2},"reference_index":2020,"source":"pdf_text","source_observed_at":"2026-08-07T11:49:05.903065Z"},"links":{"cited_paper":"/paper/2410.09403","citing_paper":"/paper/2506.01372"},"observation_digest":"sha256:c68cbb82b6b19370733072e46ec897457f42adaed0da5701ece193571d73e79f","observation_id":"e8702435-4ef3-41b9-805c-cb0e4c488351","resolution":{"observed_at":"2026-08-07T11:49:05.903065Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2001.08361","last_updated":"2020-01-23T03:59:20Z","snapshot_observed_at":"2026-07-06T08:52:12.656082Z","submitted_at":"2020-01-23T03:59:20Z","title":"Scaling Laws for Neural Language Models","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2001.08361","snapshot_observed_at":"2026-08-07T11:49:03.210248Z","title":"Scaling laws for neural language models.arXiv preprint arXiv:2001.08361,","venue":null,"work_id":null,"year":2001},"citing_paper":{"arxiv_id":"2506.01372","last_updated":"2025-06-09T09:01:24Z","snapshot_observed_at":"2026-08-09T03:01:37.763836Z","submitted_at":"2025-06-02T06:59:10Z","title":"AI Scientists Fail Without Strong Implementation Capability","version":2},"reference_index":2021,"source":"pdf_text","source_observed_at":"2026-08-07T11:49:03.210248Z"},"links":{"cited_paper":"/paper/2001.08361","citing_paper":"/paper/2506.01372"},"observation_digest":"sha256:1fdd2377ac9aca50f7e38be6e34a38d0ab0011329bfaa19a37f7ea76b2c23c1c","observation_id":"c8c668d9-075d-4330-9d09-355f19274d50","resolution":{"observed_at":"2026-08-07T11:49:03.210248Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:49:12.404985Z","title":"Genome modeling and design across all domains of life with evo 2.BioRxiv, pages 2025–02,","venue":null,"work_id":"84bcb58d-f1d5-4984-a465-a1b1603510cf","year":2025},"citing_paper":{"arxiv_id":"2506.01372","last_updated":"2025-06-09T09:01:24Z","snapshot_observed_at":"2026-08-09T03:01:37.763836Z","submitted_at":"2025-06-02T06:59:10Z","title":"AI Scientists Fail Without Strong Implementation Capability","version":2},"reference_index":2023,"source":"pdf_text","source_observed_at":"2026-08-07T11:49:01.262343Z"},"links":{"citing_paper":"/paper/2506.01372"},"observation_digest":"sha256:2d338f0a4ba86171ebe34c0042c8239fcb855af05e96cf0a29ebe77709b17e46","observation_id":"db1dceec-20e1-46cb-88b5-1ec12348c48d","resolution":{"observed_at":"2026-08-07T11:49:12.529426Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-08-07T11:49:12.631742Z","title":"Muhammad Arslan, Hussam Ghanem, Saba Munawar, and Christophe Cruz","venue":null,"work_id":"5e516ccf-e3a8-4018-924e-c6fd060320cc","year":2025},"citing_paper":{"arxiv_id":"2506.01372","last_updated":"2025-06-09T09:01:24Z","snapshot_observed_at":"2026-08-09T03:01:37.763836Z","submitted_at":"2025-06-02T06:59:10Z","title":"AI Scientists Fail Without Strong Implementation Capability","version":2},"reference_index":2024,"source":"pdf_text","source_observed_at":"2026-08-07T11:49:00.848110Z"},"links":{"citing_paper":"/paper/2506.01372"},"observation_digest":"sha256:0bea5e6e98c8d184f07260fa05f56a57c84b2169ca879ba54cf73878f942a339","observation_id":"e37c7520-1da2-45ef-b12a-a850c6209bd6","resolution":{"observed_at":"2026-08-07T11:49:12.763454Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"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":"2410.06992","last_updated":"2024-10-10T13:13:09Z","snapshot_observed_at":"2026-08-08T05:32:33.029750Z","submitted_at":"2024-10-09T15:38:53Z","title":"SWE-Bench+: Enhanced Coding Benchmark for LLMs","version":2},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2410.06992","snapshot_observed_at":"2026-08-07T11:49:00.759281Z","title":"Reem Aleithan, Haoran Xue, Mohammad Mahdi Mohajer, Elijah Nnorom, Gias Uddin, and Song Wang","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2506.01372","last_updated":"2025-06-09T09:01:24Z","snapshot_observed_at":"2026-08-09T03:01:37.763836Z","submitted_at":"2025-06-02T06:59:10Z","title":"AI Scientists Fail Without Strong Implementation Capability","version":2},"reference_index":2025,"source":"pdf_text","source_observed_at":"2026-08-07T11:49:00.759281Z"},"links":{"cited_paper":"/paper/2410.06992","citing_paper":"/paper/2506.01372"},"observation_digest":"sha256:2d83e9834803ecc97c06b4d38285b199375da485d2af0cfa17d75ff49b411839","observation_id":"03c1fc2a-f737-4294-88ae-31b39d749740","resolution":{"observed_at":"2026-08-07T11:49:00.759281Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"paper":{"arxiv_id":"2506.01372","last_updated":"2025-06-09T09:01:24Z","latest_version":2,"primary_category":"cs.AI","snapshot_observed_at":"2026-08-09T03:01:37.763836Z","submitted_at":"2025-06-02T06:59:10Z","title":"AI Scientists Fail Without Strong Implementation Capability"},"reference_resolution":{"displayed":65,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":59,"verified_exact":1,"verified_fuzzy":5},"total_outbound_references":65},"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 65 of 65 outbound references and 3 inbound Pith citation observations for arXiv:2506.01372."}