{"as_of":"2026-08-04T09:59:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:c76f1928cc82959583488916dc7fccca4ed7ce6e90c49390588956f20739dc5c","coverage":[{"denominator":39,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":39,"source":"paper_references, paper_reference_links","source_observed_at":"2026-05-23T06:39:44.542350Z","state":"measured"},{"denominator":139,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":139,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-04T06:34:03.388597+00:00","state":"measured"},{"denominator":647,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":100,"source":"paper_references, paper_reference_links","source_observed_at":"2026-05-23T19:45:39.130509Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"pith","source_observed_at":"2026-07-11T03:17:51.754565Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2412.16720","last_updated":"2026-04-30T02:46:40Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-12-21T18:04:31Z","title":"OpenAI o1 System Card","version":2},"cited_work":{"arxiv_id":"2412.16720","doi":"10.48550/arxiv.2412.16720","metadata_source":"pith","pith_arxiv_id":"2412.16720","snapshot_observed_at":"2026-07-11T03:17:51.754565Z","title":"OpenAI o1 System Card","venue":"cs.AI","work_id":"68d3c334-0fc9-49e3-b7b0-a69afae933e2","year":2024},"citing_paper":{"arxiv_id":"2410.04047","last_updated":"2026-04-10T06:16:18Z","snapshot_observed_at":"2026-07-06T19:28:18.775189Z","submitted_at":"2024-10-05T06:04:19Z","title":"TS-Reasoner: Domain-Oriented Time Series Inference Agents for Reasoning and Automated Analysis","version":6},"reference_index":54,"source":"pdf_text","source_observed_at":"2026-05-23T19:45:39.130509Z"},"links":{"cited_paper":"/paper/2412.16720","citing_paper":"/paper/2410.04047"},"observation_digest":"sha256:26a7c2cd4fea228ad2e244033ab61fda4aea23104ad31ac52c68d9929ab851ab","observation_id":"a87d7fe5-8f42-48af-8b96-967e6b73f55c","resolution":{"observed_at":"2026-05-23T19:45:47.127760Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.16720","last_updated":"2026-04-30T02:46:40Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-12-21T18:04:31Z","title":"OpenAI o1 System Card","version":2},"cited_work":{"arxiv_id":"2412.16720","doi":"10.48550/arxiv.2412.16720","metadata_source":"pith","pith_arxiv_id":"2412.16720","snapshot_observed_at":"2026-07-11T03:17:51.754565Z","title":"OpenAI o1 System Card","venue":"cs.AI","work_id":"68d3c334-0fc9-49e3-b7b0-a69afae933e2","year":2024},"citing_paper":{"arxiv_id":"2501.05366","last_updated":"2025-01-09T16:48:17Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-01-09T16:48:17Z","title":"Search-o1: Agentic Search-Enhanced Large Reasoning Models","version":1},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-05-13T17:36:27.515468Z"},"links":{"cited_paper":"/paper/2412.16720","citing_paper":"/paper/2501.05366"},"observation_digest":"sha256:a69e20c9df6252c63225537cd582fd355be3fd18c1860a40441ae8feff870c68","observation_id":"3013c957-1781-49b2-866e-847066a21a93","resolution":{"observed_at":"2026-05-13T17:36:27.705432Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.16720","last_updated":"2026-04-30T02:46:40Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-12-21T18:04:31Z","title":"OpenAI o1 System Card","version":2},"cited_work":{"arxiv_id":"2412.16720","doi":"10.48550/arxiv.2412.16720","metadata_source":"pith","pith_arxiv_id":"2412.16720","snapshot_observed_at":"2026-07-11T03:17:51.754565Z","title":"OpenAI o1 System Card","venue":"cs.AI","work_id":"68d3c334-0fc9-49e3-b7b0-a69afae933e2","year":2024},"citing_paper":{"arxiv_id":"2501.09038","last_updated":"2025-02-27T15:10:51Z","snapshot_observed_at":"2026-08-02T17:18:33.867969Z","submitted_at":"2025-01-14T20:59:37Z","title":"Do generative video models understand physical principles?","version":3},"reference_index":69,"source":"pdf_text","source_observed_at":"2026-05-20T12:47:05.825659Z"},"links":{"cited_paper":"/paper/2412.16720","citing_paper":"/paper/2501.09038"},"observation_digest":"sha256:32e3c240030c04ed6f2142c813f3dcf7d5192f613adb6b7bc2e11310f7d94337","observation_id":"0045ad51-3d30-466e-b304-68d8df5c532a","resolution":{"observed_at":"2026-05-20T12:47:05.925725Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.16720","last_updated":"2026-04-30T02:46:40Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-12-21T18:04:31Z","title":"OpenAI o1 System Card","version":2},"cited_work":{"arxiv_id":"2412.16720","doi":"10.48550/arxiv.2412.16720","metadata_source":"pith","pith_arxiv_id":"2412.16720","snapshot_observed_at":"2026-07-11T03:17:51.754565Z","title":"OpenAI o1 System Card","venue":"cs.AI","work_id":"68d3c334-0fc9-49e3-b7b0-a69afae933e2","year":2024},"citing_paper":{"arxiv_id":"2501.13918","last_updated":"2025-10-27T08:22:57Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-01-23T18:55:41Z","title":"Improving Video Generation with Human Feedback","version":2},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-05-13T15:30:02.578430Z"},"links":{"cited_paper":"/paper/2412.16720","citing_paper":"/paper/2501.13918"},"observation_digest":"sha256:06f32e7f5a7423cfe2183540dfa545e4802fb5afa494d9430993e0bb091e0130","observation_id":"30c8fa56-90d9-44b5-8ed6-5862db61a966","resolution":{"observed_at":"2026-05-13T15:30:02.664775Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.16720","last_updated":"2026-04-30T02:46:40Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-12-21T18:04:31Z","title":"OpenAI o1 System Card","version":2},"cited_work":{"arxiv_id":"2412.16720","doi":"10.48550/arxiv.2412.16720","metadata_source":"pith","pith_arxiv_id":"2412.16720","snapshot_observed_at":"2026-07-11T03:17:51.754565Z","title":"OpenAI o1 System Card","venue":"cs.AI","work_id":"68d3c334-0fc9-49e3-b7b0-a69afae933e2","year":2024},"citing_paper":{"arxiv_id":"2502.01456","last_updated":"2025-09-26T09:25:31Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-02-03T15:43:48Z","title":"Process Reinforcement through Implicit Rewards","version":2},"reference_index":77,"source":"arxiv_source","source_observed_at":"2026-05-11T20:23:30.763794Z"},"links":{"cited_paper":"/paper/2412.16720","citing_paper":"/paper/2502.01456"},"observation_digest":"sha256:37f691633cdceac87c9700159a38f58784c807a59ead7a44f2d436adcf0970a6","observation_id":"ac6228e8-fb0d-48bd-ba1a-f67e6d04c854","resolution":{"observed_at":"2026-05-11T20:23:31.182758Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.16720","last_updated":"2026-04-30T02:46:40Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-12-21T18:04:31Z","title":"OpenAI o1 System Card","version":2},"cited_work":{"arxiv_id":"2412.16720","doi":"10.48550/arxiv.2412.16720","metadata_source":"pith","pith_arxiv_id":"2412.16720","snapshot_observed_at":"2026-07-11T03:17:51.754565Z","title":"OpenAI o1 System Card","venue":"cs.AI","work_id":"68d3c334-0fc9-49e3-b7b0-a69afae933e2","year":2024},"citing_paper":{"arxiv_id":"2502.02871","last_updated":"2026-04-20T02:18:01Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-02-05T04:05:27Z","title":"Position: Multimodal Large Language Models Can Significantly Advance Scientific Reasoning","version":2},"reference_index":75,"source":"arxiv_source","source_observed_at":"2026-05-23T04:30:38.804702Z"},"links":{"cited_paper":"/paper/2412.16720","citing_paper":"/paper/2502.02871"},"observation_digest":"sha256:1dae8f08c5963f6503565102050eb7256f3e53e8c601e0eb04e308cb5e1acbc0","observation_id":"247af2f2-fda7-42d2-ac21-b9e3e720e44e","resolution":{"observed_at":"2026-05-23T04:32:32.583633Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.16720","last_updated":"2026-04-30T02:46:40Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-12-21T18:04:31Z","title":"OpenAI o1 System Card","version":2},"cited_work":{"arxiv_id":"2412.16720","doi":"10.48550/arxiv.2412.16720","metadata_source":"pith","pith_arxiv_id":"2412.16720","snapshot_observed_at":"2026-07-11T03:17:51.754565Z","title":"OpenAI o1 System Card","venue":"cs.AI","work_id":"68d3c334-0fc9-49e3-b7b0-a69afae933e2","year":2024},"citing_paper":{"arxiv_id":"2502.16810","last_updated":"2026-05-01T23:52:08Z","snapshot_observed_at":"2026-07-31T15:13:25.308192Z","submitted_at":"2025-02-24T03:36:57Z","title":"AI Realtor: Towards Grounded Persuasive Language Generation for Automated Copywriting","version":6},"reference_index":24,"source":"arxiv_source","source_observed_at":"2026-05-23T02:55:50.650423Z"},"links":{"cited_paper":"/paper/2412.16720","citing_paper":"/paper/2502.16810"},"observation_digest":"sha256:8f0bfbdfba20c854795251845deb471eda0a09381a45fda50718993c570ae65e","observation_id":"33b49f11-a4b0-4957-8bb0-581cdbf8b182","resolution":{"observed_at":"2026-05-23T02:57:26.377497Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.16720","last_updated":"2026-04-30T02:46:40Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-12-21T18:04:31Z","title":"OpenAI o1 System Card","version":2},"cited_work":{"arxiv_id":"2412.16720","doi":"10.48550/arxiv.2412.16720","metadata_source":"pith","pith_arxiv_id":"2412.16720","snapshot_observed_at":"2026-07-11T03:17:51.754565Z","title":"OpenAI o1 System Card","venue":"cs.AI","work_id":"68d3c334-0fc9-49e3-b7b0-a69afae933e2","year":2024},"citing_paper":{"arxiv_id":"2502.16982","last_updated":"2025-02-24T09:12:29Z","snapshot_observed_at":"2026-08-02T00:32:51.000665Z","submitted_at":"2025-02-24T09:12:29Z","title":"Muon is Scalable for LLM Training","version":1},"reference_index":62,"source":"arxiv_source","source_observed_at":"2026-05-11T23:02:51.656353Z"},"links":{"cited_paper":"/paper/2412.16720","citing_paper":"/paper/2502.16982"},"observation_digest":"sha256:1300b5a924a4dfc9e0c09a4737e9040d85bd2fcc59e13fed337ef32b29169349","observation_id":"a4982843-a78a-4e39-a2db-6254f9a8c684","resolution":{"observed_at":"2026-05-11T23:02:51.896015Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.16720","last_updated":"2026-04-30T02:46:40Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-12-21T18:04:31Z","title":"OpenAI o1 System Card","version":2},"cited_work":{"arxiv_id":"2412.16720","doi":"10.48550/arxiv.2412.16720","metadata_source":"pith","pith_arxiv_id":"2412.16720","snapshot_observed_at":"2026-07-11T03:17:51.754565Z","title":"OpenAI o1 System Card","venue":"cs.AI","work_id":"68d3c334-0fc9-49e3-b7b0-a69afae933e2","year":2024},"citing_paper":{"arxiv_id":"2502.18449","last_updated":"2025-12-01T00:16:59Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-02-25T18:45:04Z","title":"SWE-RL: Advancing LLM Reasoning via Reinforcement Learning on Open Software Evolution","version":2},"reference_index":40,"source":"arxiv_source","source_observed_at":"2026-05-15T10:27:56.185943Z"},"links":{"cited_paper":"/paper/2412.16720","citing_paper":"/paper/2502.18449"},"observation_digest":"sha256:13ab756a5fe2c01b22bdadfa1063193feebefbfaa899cf85fa6215153c9fae85","observation_id":"e93fdc7b-5103-4019-af05-c3f73aed22a5","resolution":{"observed_at":"2026-05-15T10:27:56.328932Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.16720","last_updated":"2026-04-30T02:46:40Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-12-21T18:04:31Z","title":"OpenAI o1 System Card","version":2},"cited_work":{"arxiv_id":"2412.16720","doi":"10.48550/arxiv.2412.16720","metadata_source":"pith","pith_arxiv_id":"2412.16720","snapshot_observed_at":"2026-07-11T03:17:51.754565Z","title":"OpenAI o1 System Card","venue":"cs.AI","work_id":"68d3c334-0fc9-49e3-b7b0-a69afae933e2","year":2024},"citing_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},"reference_index":243,"source":"arxiv_source","source_observed_at":"2026-05-11T13:02:43.571234Z"},"links":{"cited_paper":"/paper/2412.16720","citing_paper":"/paper/2502.18864"},"observation_digest":"sha256:799aa8aa6fe4548bac2a36637a18dbc90cb84274ee16024eb7ac837aa0a97b1a","observation_id":"06310081-9fd6-4ba8-a3bf-ff16916cee96","resolution":{"observed_at":"2026-05-11T13:02:45.434303Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.16720","last_updated":"2026-04-30T02:46:40Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-12-21T18:04:31Z","title":"OpenAI o1 System Card","version":2},"cited_work":{"arxiv_id":"2412.16720","doi":"10.48550/arxiv.2412.16720","metadata_source":"pith","pith_arxiv_id":"2412.16720","snapshot_observed_at":"2026-07-11T03:17:51.754565Z","title":"OpenAI o1 System Card","venue":"cs.AI","work_id":"68d3c334-0fc9-49e3-b7b0-a69afae933e2","year":2024},"citing_paper":{"arxiv_id":"2502.19918","last_updated":"2026-05-07T16:58:35Z","snapshot_observed_at":"2026-08-02T05:40:27.766263Z","submitted_at":"2025-02-27T09:40:13Z","title":"Meta-Reasoner: Dynamic Guidance for Optimized Inference-time Reasoning in Large Language Models","version":6},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-05-23T02:46:20.578680Z"},"links":{"cited_paper":"/paper/2412.16720","citing_paper":"/paper/2502.19918"},"observation_digest":"sha256:3ec1f5cc2b419ff8654f05e783bbf221925f10c64351f080c052f28ecbc7ced5","observation_id":"63212c3f-556b-4561-8b3c-fc9cf779a302","resolution":{"observed_at":"2026-05-23T02:47:26.395029Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.16720","last_updated":"2026-04-30T02:46:40Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-12-21T18:04:31Z","title":"OpenAI o1 System Card","version":2},"cited_work":{"arxiv_id":"2412.16720","doi":"10.48550/arxiv.2412.16720","metadata_source":"pith","pith_arxiv_id":"2412.16720","snapshot_observed_at":"2026-07-11T03:17:51.754565Z","title":"OpenAI o1 System Card","venue":"cs.AI","work_id":"68d3c334-0fc9-49e3-b7b0-a69afae933e2","year":2024},"citing_paper":{"arxiv_id":"2503.01785","last_updated":"2025-03-03T18:16:32Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-03-03T18:16:32Z","title":"Visual-RFT: Visual Reinforcement Fine-Tuning","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-05-13T22:16:16.528682Z"},"links":{"cited_paper":"/paper/2412.16720","citing_paper":"/paper/2503.01785"},"observation_digest":"sha256:778e2119c2206a34aae3b4c4b99f73441ed425dddd42a198659927e27bac6c28","observation_id":"b7ea3383-c815-40b3-bf78-36006e1dbdb5","resolution":{"observed_at":"2026-05-13T22:16:16.563038Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.16720","last_updated":"2026-04-30T02:46:40Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-12-21T18:04:31Z","title":"OpenAI o1 System Card","version":2},"cited_work":{"arxiv_id":"2412.16720","doi":"10.48550/arxiv.2412.16720","metadata_source":"pith","pith_arxiv_id":"2412.16720","snapshot_observed_at":"2026-07-11T03:17:51.754565Z","title":"OpenAI o1 System Card","venue":"cs.AI","work_id":"68d3c334-0fc9-49e3-b7b0-a69afae933e2","year":2024},"citing_paper":{"arxiv_id":"2503.05592","last_updated":"2025-03-18T08:32:24Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-03-07T17:14:44Z","title":"R1-Searcher: Incentivizing the Search Capability in LLMs via Reinforcement Learning","version":2},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-05-13T18:37:17.725984Z"},"links":{"cited_paper":"/paper/2412.16720","citing_paper":"/paper/2503.05592"},"observation_digest":"sha256:940546937999c75f3d61ca730d3b19d42ec27e2bc386440768965c933221dd3d","observation_id":"85a58492-8ee1-42da-8b8d-79c8c1c6f858","resolution":{"observed_at":"2026-05-13T18:37:17.800282Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.16720","last_updated":"2026-04-30T02:46:40Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-12-21T18:04:31Z","title":"OpenAI o1 System Card","version":2},"cited_work":{"arxiv_id":"2412.16720","doi":"10.48550/arxiv.2412.16720","metadata_source":"pith","pith_arxiv_id":"2412.16720","snapshot_observed_at":"2026-07-11T03:17:51.754565Z","title":"OpenAI o1 System Card","venue":"cs.AI","work_id":"68d3c334-0fc9-49e3-b7b0-a69afae933e2","year":2024},"citing_paper":{"arxiv_id":"2503.11926","last_updated":"2025-03-14T23:50:34Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-03-14T23:50:34Z","title":"Monitoring Reasoning Models for Misbehavior and the Risks of Promoting Obfuscation","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-05-21T07:24:12.845841Z"},"links":{"cited_paper":"/paper/2412.16720","citing_paper":"/paper/2503.11926"},"observation_digest":"sha256:93690da22692971dd1439dbdb14707b600dc43e1dea41f2b7581e109905f09b4","observation_id":"6c2829ad-a544-44ee-a4fa-3d06b4218630","resolution":{"observed_at":"2026-05-21T07:24:12.914288Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.16720","last_updated":"2026-04-30T02:46:40Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-12-21T18:04:31Z","title":"OpenAI o1 System Card","version":2},"cited_work":{"arxiv_id":"2412.16720","doi":"10.48550/arxiv.2412.16720","metadata_source":"pith","pith_arxiv_id":"2412.16720","snapshot_observed_at":"2026-07-11T03:17:51.754565Z","title":"OpenAI o1 System Card","venue":"cs.AI","work_id":"68d3c334-0fc9-49e3-b7b0-a69afae933e2","year":2024},"citing_paper":{"arxiv_id":"2503.12605","last_updated":"2025-03-23T13:47:43Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-03-16T18:39:13Z","title":"Multimodal Chain-of-Thought Reasoning: A Comprehensive Survey","version":2},"reference_index":216,"source":"pdf_text","source_observed_at":"2026-05-15T17:18:52.996467Z"},"links":{"cited_paper":"/paper/2412.16720","citing_paper":"/paper/2503.12605"},"observation_digest":"sha256:9c77a191efd0f2a13643caaac2fe49913987385d38cb9ce5545ed23342307f70","observation_id":"c04cd2d5-1787-4d1c-a461-bd5b979133a4","resolution":{"observed_at":"2026-05-15T17:18:53.502379Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.16720","last_updated":"2026-04-30T02:46:40Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-12-21T18:04:31Z","title":"OpenAI o1 System Card","version":2},"cited_work":{"arxiv_id":"2412.16720","doi":"10.48550/arxiv.2412.16720","metadata_source":"pith","pith_arxiv_id":"2412.16720","snapshot_observed_at":"2026-07-11T03:17:51.754565Z","title":"OpenAI o1 System Card","venue":"cs.AI","work_id":"68d3c334-0fc9-49e3-b7b0-a69afae933e2","year":2024},"citing_paper":{"arxiv_id":"2503.15558","last_updated":"2025-05-19T17:59:19Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-03-18T22:06:58Z","title":"Cosmos-Reason1: From Physical Common Sense To Embodied Reasoning","version":3},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-05-16T12:47:10.146795Z"},"links":{"cited_paper":"/paper/2412.16720","citing_paper":"/paper/2503.15558"},"observation_digest":"sha256:e396334a270e72ee48dabb55bbe7d341d9e26275cfb9f3e4d89dd6268bacc74c","observation_id":"44deceb3-f354-4082-b4ab-477a1c3d1296","resolution":{"observed_at":"2026-05-16T12:47:10.226096Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.16720","last_updated":"2026-04-30T02:46:40Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-12-21T18:04:31Z","title":"OpenAI o1 System Card","version":2},"cited_work":{"arxiv_id":"2412.16720","doi":"10.48550/arxiv.2412.16720","metadata_source":"pith","pith_arxiv_id":"2412.16720","snapshot_observed_at":"2026-07-11T03:17:51.754565Z","title":"OpenAI o1 System Card","venue":"cs.AI","work_id":"68d3c334-0fc9-49e3-b7b0-a69afae933e2","year":2024},"citing_paper":{"arxiv_id":"2503.17352","last_updated":"2025-11-11T08:13:33Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-03-21T17:52:43Z","title":"OpenVLThinker: Complex Vision-Language Reasoning via Iterative SFT-RL Cycles","version":3},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-05-19T06:59:03.112252Z"},"links":{"cited_paper":"/paper/2412.16720","citing_paper":"/paper/2503.17352"},"observation_digest":"sha256:1a38c8a250697b0fa2b4729b139c12e50f1e159fae0786f6664df7e0bb1becc7","observation_id":"6701ce42-b8d2-4c1c-92cb-5edee7514bbe","resolution":{"observed_at":"2026-05-19T06:59:03.423598Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.16720","last_updated":"2026-04-30T02:46:40Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-12-21T18:04:31Z","title":"OpenAI o1 System Card","version":2},"cited_work":{"arxiv_id":"2412.16720","doi":"10.48550/arxiv.2412.16720","metadata_source":"pith","pith_arxiv_id":"2412.16720","snapshot_observed_at":"2026-07-11T03:17:51.754565Z","title":"OpenAI o1 System Card","venue":"cs.AI","work_id":"68d3c334-0fc9-49e3-b7b0-a69afae933e2","year":2024},"citing_paper":{"arxiv_id":"2503.17599","last_updated":"2026-05-21T10:52:24Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-03-22T01:02:44Z","title":"Evaluating Clinical Competencies of Large Language Models with a General Practice Benchmark","version":3},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-05-22T23:40:25.111680Z"},"links":{"cited_paper":"/paper/2412.16720","citing_paper":"/paper/2503.17599"},"observation_digest":"sha256:f00ccd3b24ab57996b909eaa9cad93f968b9d6e345277f35102df9cb2cac4a6d","observation_id":"b0a409c1-e42e-4282-9132-06c4f8584ae8","resolution":{"observed_at":"2026-05-22T23:42:16.437331Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.16720","last_updated":"2026-04-30T02:46:40Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-12-21T18:04:31Z","title":"OpenAI o1 System Card","version":2},"cited_work":{"arxiv_id":"2412.16720","doi":"10.48550/arxiv.2412.16720","metadata_source":"pith","pith_arxiv_id":"2412.16720","snapshot_observed_at":"2026-07-11T03:17:51.754565Z","title":"OpenAI o1 System Card","venue":"cs.AI","work_id":"68d3c334-0fc9-49e3-b7b0-a69afae933e2","year":2024},"citing_paper":{"arxiv_id":"2503.21776","last_updated":"2025-10-22T16:42:24Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-03-27T17:59:51Z","title":"Video-R1: Reinforcing Video Reasoning in MLLMs","version":4},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-05-12T09:43:00.208065Z"},"links":{"cited_paper":"/paper/2412.16720","citing_paper":"/paper/2503.21776"},"observation_digest":"sha256:2dbe1fbe306ed260fa2dfd23dec4fb1f71d5e308fe98310f19a7ce83fecde995","observation_id":"0cf2566e-c90a-4846-be42-e7e1b6a8f2d5","resolution":{"observed_at":"2026-05-12T09:43:00.385402Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.16720","last_updated":"2026-04-30T02:46:40Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-12-21T18:04:31Z","title":"OpenAI o1 System Card","version":2},"cited_work":{"arxiv_id":"2412.16720","doi":"10.48550/arxiv.2412.16720","metadata_source":"pith","pith_arxiv_id":"2412.16720","snapshot_observed_at":"2026-07-11T03:17:51.754565Z","title":"OpenAI o1 System Card","venue":"cs.AI","work_id":"68d3c334-0fc9-49e3-b7b0-a69afae933e2","year":2024},"citing_paper":{"arxiv_id":"2503.22693","last_updated":"2026-05-20T06:35:51Z","snapshot_observed_at":"2026-08-02T19:43:11.453664Z","submitted_at":"2025-03-14T01:35:20Z","title":"Bridging Language Models and Financial Analysis","version":2},"reference_index":43,"source":"pdf_text","source_observed_at":"2026-05-23T01:08:58.528533Z"},"links":{"cited_paper":"/paper/2412.16720","citing_paper":"/paper/2503.22693"},"observation_digest":"sha256:33fc295a86419154ab8dc2c6722607505a670afbbdde246ec84c3a546d5a4bfe","observation_id":"ea15a7e9-e33f-40f1-9025-a53bce0b9320","resolution":{"observed_at":"2026-05-23T01:12:20.726097Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.16720","last_updated":"2026-04-30T02:46:40Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-12-21T18:04:31Z","title":"OpenAI o1 System Card","version":2},"cited_work":{"arxiv_id":"2412.16720","doi":"10.48550/arxiv.2412.16720","metadata_source":"pith","pith_arxiv_id":"2412.16720","snapshot_observed_at":"2026-07-11T03:17:51.754565Z","title":"OpenAI o1 System Card","venue":"cs.AI","work_id":"68d3c334-0fc9-49e3-b7b0-a69afae933e2","year":2024},"citing_paper":{"arxiv_id":"2504.01805","last_updated":"2025-05-21T09:38:44Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-04-02T15:12:17Z","title":"SpaceR: Reinforcing MLLMs in Video Spatial Reasoning","version":2},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-05-15T15:18:43.724432Z"},"links":{"cited_paper":"/paper/2412.16720","citing_paper":"/paper/2504.01805"},"observation_digest":"sha256:65bc1b1c1847f4d2a9fba2c1519840fa59fa51a78ef9055cb083912e55c5e191","observation_id":"fbdd8138-d05c-4863-8960-099c24d0c4c4","resolution":{"observed_at":"2026-05-15T15:18:43.800105Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.16720","last_updated":"2026-04-30T02:46:40Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-12-21T18:04:31Z","title":"OpenAI o1 System Card","version":2},"cited_work":{"arxiv_id":"2412.16720","doi":"10.48550/arxiv.2412.16720","metadata_source":"pith","pith_arxiv_id":"2412.16720","snapshot_observed_at":"2026-07-11T03:17:51.754565Z","title":"OpenAI o1 System Card","venue":"cs.AI","work_id":"68d3c334-0fc9-49e3-b7b0-a69afae933e2","year":2024},"citing_paper":{"arxiv_id":"2504.01990","last_updated":"2025-08-02T12:44:02Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-03-31T18:00:29Z","title":"Advances and Challenges in Foundation Agents: From Brain-Inspired Intelligence to Evolutionary, Collaborative, and Safe Systems","version":2},"reference_index":120,"source":"pdf_text","source_observed_at":"2026-05-22T21:39:49.832151Z"},"links":{"cited_paper":"/paper/2412.16720","citing_paper":"/paper/2504.01990"},"observation_digest":"sha256:658d6d7a9aea7487a8e1fcebd73557d55f21b89d202fd5276f454390c15e44e0","observation_id":"60ec13ed-666c-43f1-abe2-ff8eb4a168f0","resolution":{"observed_at":"2026-05-22T21:42:10.639806Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.16720","last_updated":"2026-04-30T02:46:40Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-12-21T18:04:31Z","title":"OpenAI o1 System Card","version":2},"cited_work":{"arxiv_id":"2412.16720","doi":"10.48550/arxiv.2412.16720","metadata_source":"pith","pith_arxiv_id":"2412.16720","snapshot_observed_at":"2026-07-11T03:17:51.754565Z","title":"OpenAI o1 System Card","venue":"cs.AI","work_id":"68d3c334-0fc9-49e3-b7b0-a69afae933e2","year":2024},"citing_paper":{"arxiv_id":"2504.02181","last_updated":"2026-04-22T01:49:17Z","snapshot_observed_at":"2026-07-30T09:24:14.725185Z","submitted_at":"2025-04-02T23:51:27Z","title":"A Survey of Scaling in Large Language Model Reasoning","version":2},"reference_index":66,"source":"pdf_text","source_observed_at":"2026-05-22T21:20:07.238992Z"},"links":{"cited_paper":"/paper/2412.16720","citing_paper":"/paper/2504.02181"},"observation_digest":"sha256:e86e3dbe9b2e60b16a2602f0a635ab946ac67985396b4fd76be935165a3ab952","observation_id":"6a066174-9168-4cb0-b197-bdb1bb7b3283","resolution":{"observed_at":"2026-05-22T21:22:08.995753Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.16720","last_updated":"2026-04-30T02:46:40Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-12-21T18:04:31Z","title":"OpenAI o1 System Card","version":2},"cited_work":{"arxiv_id":"2412.16720","doi":"10.48550/arxiv.2412.16720","metadata_source":"pith","pith_arxiv_id":"2412.16720","snapshot_observed_at":"2026-07-11T03:17:51.754565Z","title":"OpenAI o1 System Card","venue":"cs.AI","work_id":"68d3c334-0fc9-49e3-b7b0-a69afae933e2","year":2024},"citing_paper":{"arxiv_id":"2504.02605","last_updated":"2025-04-03T14:06:17Z","snapshot_observed_at":"2026-07-30T07:56:48.878578Z","submitted_at":"2025-04-03T14:06:17Z","title":"Multi-SWE-bench: A Multilingual Benchmark for Issue Resolving","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-05-16T06:48:50.416649Z"},"links":{"cited_paper":"/paper/2412.16720","citing_paper":"/paper/2504.02605"},"observation_digest":"sha256:544760d27e71c0f84c87303522f32e5a30c992e7119c2bd33adfdfb870e07649","observation_id":"0cf83429-94ea-4017-be87-be23f6a76d4c","resolution":{"observed_at":"2026-05-16T06:48:50.529394Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.16720","last_updated":"2026-04-30T02:46:40Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-12-21T18:04:31Z","title":"OpenAI o1 System Card","version":2},"cited_work":{"arxiv_id":"2412.16720","doi":"10.48550/arxiv.2412.16720","metadata_source":"pith","pith_arxiv_id":"2412.16720","snapshot_observed_at":"2026-07-11T03:17:51.754565Z","title":"OpenAI o1 System Card","venue":"cs.AI","work_id":"68d3c334-0fc9-49e3-b7b0-a69afae933e2","year":2024},"citing_paper":{"arxiv_id":"2504.05605","last_updated":"2025-04-08T01:36:16Z","snapshot_observed_at":"2026-08-02T05:27:21.658804Z","submitted_at":"2025-04-08T01:36:16Z","title":"ShadowCoT: Cognitive Hijacking for Stealthy Reasoning Backdoors in LLMs","version":1},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-05-22T21:11:46.405944Z"},"links":{"cited_paper":"/paper/2412.16720","citing_paper":"/paper/2504.05605"},"observation_digest":"sha256:fe0869c19503b471dbc9e8e9551918a8bfcbb576bcc5f52b66865e3a3df4d9bc","observation_id":"75282cc6-5315-47a0-ad5b-470a9ebcc7e8","resolution":{"observed_at":"2026-05-22T21:12:08.401342Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.16720","last_updated":"2026-04-30T02:46:40Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-12-21T18:04:31Z","title":"OpenAI o1 System Card","version":2},"cited_work":{"arxiv_id":"2412.16720","doi":"10.48550/arxiv.2412.16720","metadata_source":"pith","pith_arxiv_id":"2412.16720","snapshot_observed_at":"2026-07-11T03:17:51.754565Z","title":"OpenAI o1 System Card","venue":"cs.AI","work_id":"68d3c334-0fc9-49e3-b7b0-a69afae933e2","year":2024},"citing_paper":{"arxiv_id":"2504.06958","last_updated":"2025-11-11T08:30:00Z","snapshot_observed_at":"2026-08-02T02:31:33.589341Z","submitted_at":"2025-04-09T15:09:27Z","title":"VideoChat-R1: Enhancing Spatio-Temporal Perception via Reinforcement Fine-Tuning","version":5},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-05-15T20:56:07.247122Z"},"links":{"cited_paper":"/paper/2412.16720","citing_paper":"/paper/2504.06958"},"observation_digest":"sha256:b6912ce5359d42e607e2a98166f2a73132af27a7a1779dfa20fe03175c3aafff","observation_id":"4b2d7e38-b69b-412e-852b-4cdb9c56169f","resolution":{"observed_at":"2026-05-15T20:56:07.800834Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.16720","last_updated":"2026-04-30T02:46:40Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-12-21T18:04:31Z","title":"OpenAI o1 System Card","version":2},"cited_work":{"arxiv_id":"2412.16720","doi":"10.48550/arxiv.2412.16720","metadata_source":"pith","pith_arxiv_id":"2412.16720","snapshot_observed_at":"2026-07-11T03:17:51.754565Z","title":"OpenAI o1 System Card","venue":"cs.AI","work_id":"68d3c334-0fc9-49e3-b7b0-a69afae933e2","year":2024},"citing_paper":{"arxiv_id":"2504.07615","last_updated":"2025-04-14T15:15:54Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-04-10T10:05:15Z","title":"VLM-R1: A Stable and Generalizable R1-style Large Vision-Language Model","version":2},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-05-13T01:13:57.368874Z"},"links":{"cited_paper":"/paper/2412.16720","citing_paper":"/paper/2504.07615"},"observation_digest":"sha256:c50d90ed5c05f18920a7d773361581bc29e3c0cd92bcd658feb1804d6765e328","observation_id":"92a507b0-ac44-4c86-98cf-444840ef807a","resolution":{"observed_at":"2026-05-13T01:13:57.428243Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.16720","last_updated":"2026-04-30T02:46:40Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-12-21T18:04:31Z","title":"OpenAI o1 System Card","version":2},"cited_work":{"arxiv_id":"2412.16720","doi":"10.48550/arxiv.2412.16720","metadata_source":"pith","pith_arxiv_id":"2412.16720","snapshot_observed_at":"2026-07-11T03:17:51.754565Z","title":"OpenAI o1 System Card","venue":"cs.AI","work_id":"68d3c334-0fc9-49e3-b7b0-a69afae933e2","year":2024},"citing_paper":{"arxiv_id":"2504.10458","last_updated":"2025-10-01T04:55:20Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-04-14T17:45:54Z","title":"GUI-R1 : A Generalist R1-Style Vision-Language Action Model For GUI Agents","version":4},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-05-15T02:10:57.976448Z"},"links":{"cited_paper":"/paper/2412.16720","citing_paper":"/paper/2504.10458"},"observation_digest":"sha256:1a36816a4a492bdee1f680f45c652cf84f8e0e497eb16cd9b891d2a55398726e","observation_id":"e12da7af-c7d4-4a2f-8663-5ec32075f7e5","resolution":{"observed_at":"2026-05-15T02:10:58.058469Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.16720","last_updated":"2026-04-30T02:46:40Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-12-21T18:04:31Z","title":"OpenAI o1 System Card","version":2},"cited_work":{"arxiv_id":"2412.16720","doi":"10.48550/arxiv.2412.16720","metadata_source":"pith","pith_arxiv_id":"2412.16720","snapshot_observed_at":"2026-07-11T03:17:51.754565Z","title":"OpenAI o1 System Card","venue":"cs.AI","work_id":"68d3c334-0fc9-49e3-b7b0-a69afae933e2","year":2024},"citing_paper":{"arxiv_id":"2504.11536","last_updated":"2025-04-17T16:46:07Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-04-15T18:10:22Z","title":"ReTool: Reinforcement Learning for Strategic Tool Use in LLMs","version":2},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-05-13T18:42:39.023650Z"},"links":{"cited_paper":"/paper/2412.16720","citing_paper":"/paper/2504.11536"},"observation_digest":"sha256:8b4e5bcb442ce24799d4cfb013f1fa6793eadbe9f3372cea9e35c38eb22bf19f","observation_id":"2f799563-72cb-4508-bdb3-6ec36705170a","resolution":{"observed_at":"2026-05-13T18:42:39.085744Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.16720","last_updated":"2026-04-30T02:46:40Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-12-21T18:04:31Z","title":"OpenAI o1 System Card","version":2},"cited_work":{"arxiv_id":"2412.16720","doi":"10.48550/arxiv.2412.16720","metadata_source":"pith","pith_arxiv_id":"2412.16720","snapshot_observed_at":"2026-07-11T03:17:51.754565Z","title":"OpenAI o1 System Card","venue":"cs.AI","work_id":"68d3c334-0fc9-49e3-b7b0-a69afae933e2","year":2024},"citing_paper":{"arxiv_id":"2504.13818","last_updated":"2026-04-22T00:26:08Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-04-18T17:49:55Z","title":"Not All Rollouts are Useful: Down-Sampling Rollouts in LLM Reinforcement Learning","version":5},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-05-22T18:46:11.571831Z"},"links":{"cited_paper":"/paper/2412.16720","citing_paper":"/paper/2504.13818"},"observation_digest":"sha256:9708509b17702ba3348d9b1e1513937ec0aa735e1fd7533c6f9310b59da959b3","observation_id":"a6ef537b-c81e-412e-b23b-26bfd411b764","resolution":{"observed_at":"2026-05-22T18:46:56.911247Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.16720","last_updated":"2026-04-30T02:46:40Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-12-21T18:04:31Z","title":"OpenAI o1 System Card","version":2},"cited_work":{"arxiv_id":"2412.16720","doi":"10.48550/arxiv.2412.16720","metadata_source":"pith","pith_arxiv_id":"2412.16720","snapshot_observed_at":"2026-07-11T03:17:51.754565Z","title":"OpenAI o1 System Card","venue":"cs.AI","work_id":"68d3c334-0fc9-49e3-b7b0-a69afae933e2","year":2024},"citing_paper":{"arxiv_id":"2504.13898","last_updated":"2026-05-12T14:42:20Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-04-07T06:27:02Z","title":"Social Human Robot Embodied Conversation (SHREC) Dataset: Benchmarking Foundational Models' Social Reasoning","version":3},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-05-22T21:14:13.351140Z"},"links":{"cited_paper":"/paper/2412.16720","citing_paper":"/paper/2504.13898"},"observation_digest":"sha256:d7c089f71b94b3fa668cdf6ec8785ccd4ae824470c3aa02a71a0a1332ad608bb","observation_id":"5ca418fd-412b-48a8-a360-de6e2d5c0104","resolution":{"observed_at":"2026-05-22T21:15:09.416470Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.16720","last_updated":"2026-04-30T02:46:40Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-12-21T18:04:31Z","title":"OpenAI o1 System Card","version":2},"cited_work":{"arxiv_id":"2412.16720","doi":"10.48550/arxiv.2412.16720","metadata_source":"pith","pith_arxiv_id":"2412.16720","snapshot_observed_at":"2026-07-11T03:17:51.754565Z","title":"OpenAI o1 System Card","venue":"cs.AI","work_id":"68d3c334-0fc9-49e3-b7b0-a69afae933e2","year":2024},"citing_paper":{"arxiv_id":"2504.14945","last_updated":"2025-06-22T00:18:09Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-04-21T08:09:13Z","title":"Learning to Reason under Off-Policy Guidance","version":5},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-05-15T23:17:02.701393Z"},"links":{"cited_paper":"/paper/2412.16720","citing_paper":"/paper/2504.14945"},"observation_digest":"sha256:3b122699143e9630517d0f8ca36659c0e00a516a8aad77a81d0ee1e6618dd5f3","observation_id":"d338cd94-29c7-4259-a619-212b68198297","resolution":{"observed_at":"2026-05-15T23:17:02.747172Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.16720","last_updated":"2026-04-30T02:46:40Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-12-21T18:04:31Z","title":"OpenAI o1 System Card","version":2},"cited_work":{"arxiv_id":"2412.16720","doi":"10.48550/arxiv.2412.16720","metadata_source":"pith","pith_arxiv_id":"2412.16720","snapshot_observed_at":"2026-07-11T03:17:51.754565Z","title":"OpenAI o1 System Card","venue":"cs.AI","work_id":"68d3c334-0fc9-49e3-b7b0-a69afae933e2","year":2024},"citing_paper":{"arxiv_id":"2504.16054","last_updated":"2025-04-22T17:31:29Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-04-22T17:31:29Z","title":"$\\pi_{0.5}$: a Vision-Language-Action Model with Open-World Generalization","version":1},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-05-22T18:02:23.305313Z"},"links":{"cited_paper":"/paper/2412.16720","citing_paper":"/paper/2504.16054"},"observation_digest":"sha256:5527e15dac67464bdece4f68b7bd58a471ee0b501deeba7f5ab2d8bd7f05484b","observation_id":"03668529-d3c6-4f04-9439-a58281f01c53","resolution":{"observed_at":"2026-05-22T18:05:00.899688Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.16720","last_updated":"2026-04-30T02:46:40Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-12-21T18:04:31Z","title":"OpenAI o1 System Card","version":2},"cited_work":{"arxiv_id":"2412.16720","doi":"10.48550/arxiv.2412.16720","metadata_source":"pith","pith_arxiv_id":"2412.16720","snapshot_observed_at":"2026-07-11T03:17:51.754565Z","title":"OpenAI o1 System Card","venue":"cs.AI","work_id":"68d3c334-0fc9-49e3-b7b0-a69afae933e2","year":2024},"citing_paper":{"arxiv_id":"2504.19678","last_updated":"2026-03-06T19:01:27Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-04-28T11:08:22Z","title":"From LLM Reasoning to Autonomous AI Agents: A Comprehensive Review","version":2},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-05-15T02:57:37.873567Z"},"links":{"cited_paper":"/paper/2412.16720","citing_paper":"/paper/2504.19678"},"observation_digest":"sha256:9af0327e28364213beb55827ac6d6f633f97b29243cf42c8358800eab742acc5","observation_id":"902665c1-daf6-4479-9037-ec529293c028","resolution":{"observed_at":"2026-05-15T02:57:38.197200Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.16720","last_updated":"2026-04-30T02:46:40Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-12-21T18:04:31Z","title":"OpenAI o1 System Card","version":2},"cited_work":{"arxiv_id":"2412.16720","doi":"10.48550/arxiv.2412.16720","metadata_source":"pith","pith_arxiv_id":"2412.16720","snapshot_observed_at":"2026-07-11T03:17:51.754565Z","title":"OpenAI o1 System Card","venue":"cs.AI","work_id":"68d3c334-0fc9-49e3-b7b0-a69afae933e2","year":2024},"citing_paper":{"arxiv_id":"2504.21318","last_updated":"2025-04-30T05:05:09Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-04-30T05:05:09Z","title":"Phi-4-reasoning Technical Report","version":1},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-05-17T03:40:25.706499Z"},"links":{"cited_paper":"/paper/2412.16720","citing_paper":"/paper/2504.21318"},"observation_digest":"sha256:da1f9d6bc1a9917d0b654db1a03766c9c5840f5acee59e45cd6046b69ced9cd6","observation_id":"879aa7e9-f46d-4dd6-891b-6f41031ca8e6","resolution":{"observed_at":"2026-05-17T03:40:25.786192Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.16720","last_updated":"2026-04-30T02:46:40Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-12-21T18:04:31Z","title":"OpenAI o1 System Card","version":2},"cited_work":{"arxiv_id":"2412.16720","doi":"10.48550/arxiv.2412.16720","metadata_source":"pith","pith_arxiv_id":"2412.16720","snapshot_observed_at":"2026-07-11T03:17:51.754565Z","title":"OpenAI o1 System Card","venue":"cs.AI","work_id":"68d3c334-0fc9-49e3-b7b0-a69afae933e2","year":2024},"citing_paper":{"arxiv_id":"2504.21776","last_updated":"2025-10-13T12:40:15Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-04-30T16:25:25Z","title":"WebThinker: Empowering Large Reasoning Models with Deep Research Capability","version":2},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-05-16T19:14:25.283645Z"},"links":{"cited_paper":"/paper/2412.16720","citing_paper":"/paper/2504.21776"},"observation_digest":"sha256:9be9bbe0c71d4b6aa540e8307593ddd9e5c63b172ef2a9e581286631c31b21ea","observation_id":"dec3357e-4eec-4c7e-9fb7-70b17baafa75","resolution":{"observed_at":"2026-05-16T19:14:25.421358Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.16720","last_updated":"2026-04-30T02:46:40Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-12-21T18:04:31Z","title":"OpenAI o1 System Card","version":2},"cited_work":{"arxiv_id":"2412.16720","doi":"10.48550/arxiv.2412.16720","metadata_source":"pith","pith_arxiv_id":"2412.16720","snapshot_observed_at":"2026-07-11T03:17:51.754565Z","title":"OpenAI o1 System Card","venue":"cs.AI","work_id":"68d3c334-0fc9-49e3-b7b0-a69afae933e2","year":2024},"citing_paper":{"arxiv_id":"2505.04638","last_updated":"2026-04-06T18:12:55Z","snapshot_observed_at":"2026-08-01T16:43:54.783975Z","submitted_at":"2025-05-03T14:21:48Z","title":"Advancing AI Research Assistants with Expert-Involved Learning","version":5},"reference_index":57,"source":"pdf_text","source_observed_at":"2026-05-22T16:20:33.081589Z"},"links":{"cited_paper":"/paper/2412.16720","citing_paper":"/paper/2505.04638"},"observation_digest":"sha256:13440925010cdb434c8b115a5a24b117f8c09c72209b26d1a66b92f72a07b617","observation_id":"0cc94186-6181-44d7-9cba-ebd39fad8a25","resolution":{"observed_at":"2026-05-22T16:21:46.999231Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.16720","last_updated":"2026-04-30T02:46:40Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-12-21T18:04:31Z","title":"OpenAI o1 System Card","version":2},"cited_work":{"arxiv_id":"2412.16720","doi":"10.48550/arxiv.2412.16720","metadata_source":"pith","pith_arxiv_id":"2412.16720","snapshot_observed_at":"2026-07-11T03:17:51.754565Z","title":"OpenAI o1 System Card","venue":"cs.AI","work_id":"68d3c334-0fc9-49e3-b7b0-a69afae933e2","year":2024},"citing_paper":{"arxiv_id":"2505.05470","last_updated":"2025-10-27T09:57:02Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-05-08T17:58:45Z","title":"Flow-GRPO: Training Flow Matching Models via Online RL","version":5},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-05-11T18:45:16.641012Z"},"links":{"cited_paper":"/paper/2412.16720","citing_paper":"/paper/2505.05470"},"observation_digest":"sha256:f442387c75daf43c0e85e0b786efcf79245500d1afb87dae66b4ee8812be5e02","observation_id":"30e6b102-5b03-4426-951b-9c195864eefc","resolution":{"observed_at":"2026-05-11T18:45:16.776277Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.16720","last_updated":"2026-04-30T02:46:40Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-12-21T18:04:31Z","title":"OpenAI o1 System Card","version":2},"cited_work":{"arxiv_id":"2412.16720","doi":"10.48550/arxiv.2412.16720","metadata_source":"pith","pith_arxiv_id":"2412.16720","snapshot_observed_at":"2026-07-11T03:17:51.754565Z","title":"OpenAI o1 System Card","venue":"cs.AI","work_id":"68d3c334-0fc9-49e3-b7b0-a69afae933e2","year":2024},"citing_paper":{"arxiv_id":"2505.07062","last_updated":"2025-05-11T17:28:30Z","snapshot_observed_at":"2026-08-02T16:13:31.498470Z","submitted_at":"2025-05-11T17:28:30Z","title":"Seed1.5-VL Technical Report","version":1},"reference_index":56,"source":"pdf_text","source_observed_at":"2026-05-11T05:26:04.960844Z"},"links":{"cited_paper":"/paper/2412.16720","citing_paper":"/paper/2505.07062"},"observation_digest":"sha256:dbb96de4f0b7314006ba9069f64c9a1251f9546f523556245b63f8c568469596","observation_id":"b05d473d-0521-41c9-a644-524f69447186","resolution":{"observed_at":"2026-05-11T05:26:05.415512Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.16720","last_updated":"2026-04-30T02:46:40Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-12-21T18:04:31Z","title":"OpenAI o1 System Card","version":2},"cited_work":{"arxiv_id":"2412.16720","doi":"10.48550/arxiv.2412.16720","metadata_source":"pith","pith_arxiv_id":"2412.16720","snapshot_observed_at":"2026-07-11T03:17:51.754565Z","title":"OpenAI o1 System Card","venue":"cs.AI","work_id":"68d3c334-0fc9-49e3-b7b0-a69afae933e2","year":2024},"citing_paper":{"arxiv_id":"2505.12601","last_updated":"2026-05-14T18:08:42Z","snapshot_observed_at":"2026-08-02T11:09:30.375825Z","submitted_at":"2025-05-19T01:33:41Z","title":"Rethinking Predictive Modeling for LLM Routing: When Simple kNN Beats Complex Learned Routers","version":2},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-05-22T15:13:28.927880Z"},"links":{"cited_paper":"/paper/2412.16720","citing_paper":"/paper/2505.12601"},"observation_digest":"sha256:9b150486d52f80ac79d8fe4c4e0838bb90340b60f1ce7139f38120e77f771990","observation_id":"18b08c78-c2b4-4dc3-9480-a331cc211f6c","resolution":{"observed_at":"2026-05-22T15:14:57.376399Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.16720","last_updated":"2026-04-30T02:46:40Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-12-21T18:04:31Z","title":"OpenAI o1 System Card","version":2},"cited_work":{"arxiv_id":"2412.16720","doi":"10.48550/arxiv.2412.16720","metadata_source":"pith","pith_arxiv_id":"2412.16720","snapshot_observed_at":"2026-07-11T03:17:51.754565Z","title":"OpenAI o1 System Card","venue":"cs.AI","work_id":"68d3c334-0fc9-49e3-b7b0-a69afae933e2","year":2024},"citing_paper":{"arxiv_id":"2505.14683","last_updated":"2025-07-27T11:45:16Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-05-20T17:59:30Z","title":"Emerging Properties in Unified Multimodal Pretraining","version":3},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-05-10T16:23:41.854132Z"},"links":{"cited_paper":"/paper/2412.16720","citing_paper":"/paper/2505.14683"},"observation_digest":"sha256:3eed6f6b2fe9dc9808e75216cf6d04dee2e49a66be8370ef92b8a9d53b8d0af9","observation_id":"a646fe81-ce53-4519-b4ca-cb97f0e5b60d","resolution":{"observed_at":"2026-05-10T16:23:41.960242Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.16720","last_updated":"2026-04-30T02:46:40Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-12-21T18:04:31Z","title":"OpenAI o1 System Card","version":2},"cited_work":{"arxiv_id":"2412.16720","doi":"10.48550/arxiv.2412.16720","metadata_source":"pith","pith_arxiv_id":"2412.16720","snapshot_observed_at":"2026-07-11T03:17:51.754565Z","title":"OpenAI o1 System Card","venue":"cs.AI","work_id":"68d3c334-0fc9-49e3-b7b0-a69afae933e2","year":2024},"citing_paper":{"arxiv_id":"2505.15436","last_updated":"2025-12-05T05:44:39Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-05-21T12:18:15Z","title":"Adaptive Chain-of-Focus Reasoning via Dynamic Visual Search and Zooming for Efficient VLMs","version":3},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-05-17T05:35:13.118221Z"},"links":{"cited_paper":"/paper/2412.16720","citing_paper":"/paper/2505.15436"},"observation_digest":"sha256:3eb9f29201703684b569033f8db67884d74ea0f57c6f99e8cc4cd1e59e0b2887","observation_id":"3af291e3-d4b8-4c09-b2fb-b2ecac70fdae","resolution":{"observed_at":"2026-05-17T05:35:13.261520Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.16720","last_updated":"2026-04-30T02:46:40Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-12-21T18:04:31Z","title":"OpenAI o1 System Card","version":2},"cited_work":{"arxiv_id":"2412.16720","doi":"10.48550/arxiv.2412.16720","metadata_source":"pith","pith_arxiv_id":"2412.16720","snapshot_observed_at":"2026-07-11T03:17:51.754565Z","title":"OpenAI o1 System Card","venue":"cs.AI","work_id":"68d3c334-0fc9-49e3-b7b0-a69afae933e2","year":2024},"citing_paper":{"arxiv_id":"2505.15809","last_updated":"2025-09-25T02:40:45Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-05-21T17:59:05Z","title":"MMaDA: Multimodal Large Diffusion Language Models","version":2},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-05-15T14:50:59.661153Z"},"links":{"cited_paper":"/paper/2412.16720","citing_paper":"/paper/2505.15809"},"observation_digest":"sha256:e13f0b7e730755a4347a9ab33b5a6b844f4acf9b594dbfb9219058c31cd327c2","observation_id":"921f9849-59d5-4d60-a968-b371ad70fa52","resolution":{"observed_at":"2026-05-15T14:50:59.729150Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.16720","last_updated":"2026-04-30T02:46:40Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-12-21T18:04:31Z","title":"OpenAI o1 System Card","version":2},"cited_work":{"arxiv_id":"2412.16720","doi":"10.48550/arxiv.2412.16720","metadata_source":"pith","pith_arxiv_id":"2412.16720","snapshot_observed_at":"2026-07-11T03:17:51.754565Z","title":"OpenAI o1 System Card","venue":"cs.AI","work_id":"68d3c334-0fc9-49e3-b7b0-a69afae933e2","year":2024},"citing_paper":{"arxiv_id":"2505.17123","last_updated":"2026-05-21T12:25:44Z","snapshot_observed_at":"2026-08-03T06:01:46.333933Z","submitted_at":"2025-05-21T17:59:12Z","title":"MTR-Bench: A Comprehensive Benchmark for Multi-Turn Reasoning Evaluation","version":3},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-05-22T13:37:49.475416Z"},"links":{"cited_paper":"/paper/2412.16720","citing_paper":"/paper/2505.17123"},"observation_digest":"sha256:8b97146bebf266151d5daa928d510e06d64f8860d7fc07981646976305af0af2","observation_id":"12a2dcaf-e7f7-45eb-9be8-d71c6ad64e74","resolution":{"observed_at":"2026-05-22T13:41:36.714487Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.16720","last_updated":"2026-04-30T02:46:40Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-12-21T18:04:31Z","title":"OpenAI o1 System Card","version":2},"cited_work":{"arxiv_id":"2412.16720","doi":"10.48550/arxiv.2412.16720","metadata_source":"pith","pith_arxiv_id":"2412.16720","snapshot_observed_at":"2026-07-11T03:17:51.754565Z","title":"OpenAI o1 System Card","venue":"cs.AI","work_id":"68d3c334-0fc9-49e3-b7b0-a69afae933e2","year":2024},"citing_paper":{"arxiv_id":"2505.22312","last_updated":"2025-05-29T09:07:33Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-05-28T12:56:04Z","title":"Skywork Open Reasoner 1 Technical Report","version":2},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-05-17T04:26:47.283983Z"},"links":{"cited_paper":"/paper/2412.16720","citing_paper":"/paper/2505.22312"},"observation_digest":"sha256:b950f315fc9e36caafa33debb3e2229b2d18d47cb498625301b8441c90cb91d0","observation_id":"30b1bc61-6135-40ab-8d77-62600898ec20","resolution":{"observed_at":"2026-05-17T04:26:47.321986Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.16720","last_updated":"2026-04-30T02:46:40Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-12-21T18:04:31Z","title":"OpenAI o1 System Card","version":2},"cited_work":{"arxiv_id":"2412.16720","doi":"10.48550/arxiv.2412.16720","metadata_source":"pith","pith_arxiv_id":"2412.16720","snapshot_observed_at":"2026-07-11T03:17:51.754565Z","title":"OpenAI o1 System Card","venue":"cs.AI","work_id":"68d3c334-0fc9-49e3-b7b0-a69afae933e2","year":2024},"citing_paper":{"arxiv_id":"2505.23281","last_updated":"2026-01-14T21:39:58Z","snapshot_observed_at":"2026-08-02T10:05:44.330694Z","submitted_at":"2025-05-29T09:28:06Z","title":"MathArena: Evaluating LLMs on Uncontaminated Math Competitions","version":3},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-05-15T00:10:14.812539Z"},"links":{"cited_paper":"/paper/2412.16720","citing_paper":"/paper/2505.23281"},"observation_digest":"sha256:e1782f7d3073f04de43b711ad84a83d254874c5b8452272e30652ec9f3613fef","observation_id":"f31bc8ac-ce04-4f28-9c57-eefb17f55c9c","resolution":{"observed_at":"2026-05-15T00:10:14.853634Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.16720","last_updated":"2026-04-30T02:46:40Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-12-21T18:04:31Z","title":"OpenAI o1 System Card","version":2},"cited_work":{"arxiv_id":"2412.16720","doi":"10.48550/arxiv.2412.16720","metadata_source":"pith","pith_arxiv_id":"2412.16720","snapshot_observed_at":"2026-07-11T03:17:51.754565Z","title":"OpenAI o1 System Card","venue":"cs.AI","work_id":"68d3c334-0fc9-49e3-b7b0-a69afae933e2","year":2024},"citing_paper":{"arxiv_id":"2505.23678","last_updated":"2026-05-15T17:27:46Z","snapshot_observed_at":"2026-08-02T04:30:21.704758Z","submitted_at":"2025-05-29T17:20:26Z","title":"Grounded Reinforcement Learning for Visual Reasoning","version":3},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-05-22T01:05:18.801388Z"},"links":{"cited_paper":"/paper/2412.16720","citing_paper":"/paper/2505.23678"},"observation_digest":"sha256:c8c562267b65b12035604c8f01002a4737b90e928fd8d157d165c712abaa18e6","observation_id":"e9727c17-25ee-4a35-b0bc-d4ad5e91090d","resolution":{"observed_at":"2026-05-22T01:05:51.914863Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.16720","last_updated":"2026-04-30T02:46:40Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-12-21T18:04:31Z","title":"OpenAI o1 System Card","version":2},"cited_work":{"arxiv_id":"2412.16720","doi":"10.48550/arxiv.2412.16720","metadata_source":"pith","pith_arxiv_id":"2412.16720","snapshot_observed_at":"2026-07-11T03:17:51.754565Z","title":"OpenAI o1 System Card","venue":"cs.AI","work_id":"68d3c334-0fc9-49e3-b7b0-a69afae933e2","year":2024},"citing_paper":{"arxiv_id":"2505.24864","last_updated":"2025-05-30T17:59:01Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-05-30T17:59:01Z","title":"ProRL: Prolonged Reinforcement Learning Expands Reasoning Boundaries in Large Language Models","version":1},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-05-18T20:52:33.620041Z"},"links":{"cited_paper":"/paper/2412.16720","citing_paper":"/paper/2505.24864"},"observation_digest":"sha256:faa19917190d1d381017f68a56259647b61fecf1bd1c7e4211843cde5622f707","observation_id":"db55c592-fee7-489c-917f-8a715bd1b81f","resolution":{"observed_at":"2026-05-18T20:52:33.737148Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.16720","last_updated":"2026-04-30T02:46:40Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-12-21T18:04:31Z","title":"OpenAI o1 System Card","version":2},"cited_work":{"arxiv_id":"2412.16720","doi":"10.48550/arxiv.2412.16720","metadata_source":"pith","pith_arxiv_id":"2412.16720","snapshot_observed_at":"2026-07-11T03:17:51.754565Z","title":"OpenAI o1 System Card","venue":"cs.AI","work_id":"68d3c334-0fc9-49e3-b7b0-a69afae933e2","year":2024},"citing_paper":{"arxiv_id":"2506.06414","last_updated":"2026-04-20T20:58:30Z","snapshot_observed_at":"2026-08-03T02:03:44.971897Z","submitted_at":"2025-06-06T17:33:33Z","title":"Benchmarking Misuse Mitigation Against Covert Adversaries","version":2},"reference_index":57,"source":"pdf_text","source_observed_at":"2026-05-19T10:29:05.104520Z"},"links":{"cited_paper":"/paper/2412.16720","citing_paper":"/paper/2506.06414"},"observation_digest":"sha256:42686685cf6c5f8547045a4543aebba3337a37a12e9432e28317f9ea23ec754f","observation_id":"69416a9f-dd28-4c49-b1e9-5fd73251f25c","resolution":{"observed_at":"2026-05-19T10:32:14.748083Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.16720","last_updated":"2026-04-30T02:46:40Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-12-21T18:04:31Z","title":"OpenAI o1 System Card","version":2},"cited_work":{"arxiv_id":"2412.16720","doi":"10.48550/arxiv.2412.16720","metadata_source":"pith","pith_arxiv_id":"2412.16720","snapshot_observed_at":"2026-07-11T03:17:51.754565Z","title":"OpenAI o1 System Card","venue":"cs.AI","work_id":"68d3c334-0fc9-49e3-b7b0-a69afae933e2","year":2024},"citing_paper":{"arxiv_id":"2506.06941","last_updated":"2025-11-20T00:19:24Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-06-07T22:42:29Z","title":"The Illusion of Thinking: Understanding the Strengths and Limitations of Reasoning Models via the Lens of Problem Complexity","version":3},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-05-15T16:10:31.440921Z"},"links":{"cited_paper":"/paper/2412.16720","citing_paper":"/paper/2506.06941"},"observation_digest":"sha256:296c8cfc9391522e6936dc6451092ebe8724e9c8a1aa7eb01539c80be48da629","observation_id":"74edeebe-70c6-4f31-bc0d-81d9dd587ff4","resolution":{"observed_at":"2026-05-15T16:10:31.670387Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.16720","last_updated":"2026-04-30T02:46:40Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-12-21T18:04:31Z","title":"OpenAI o1 System Card","version":2},"cited_work":{"arxiv_id":"2412.16720","doi":"10.48550/arxiv.2412.16720","metadata_source":"pith","pith_arxiv_id":"2412.16720","snapshot_observed_at":"2026-07-11T03:17:51.754565Z","title":"OpenAI o1 System Card","venue":"cs.AI","work_id":"68d3c334-0fc9-49e3-b7b0-a69afae933e2","year":2024},"citing_paper":{"arxiv_id":"2506.09965","last_updated":"2025-06-19T03:46:55Z","snapshot_observed_at":"2026-07-31T21:40:49.363128Z","submitted_at":"2025-06-11T17:41:50Z","title":"Reinforcing Spatial Reasoning in Vision-Language Models with Interwoven Thinking and Visual Drawing","version":2},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-05-17T04:58:10.202784Z"},"links":{"cited_paper":"/paper/2412.16720","citing_paper":"/paper/2506.09965"},"observation_digest":"sha256:a2a627f435bd54e9d9e19dcd1e495d45f1b0d96f49019b02d0d0d00a87206dde","observation_id":"40aed62e-98cf-485d-9dd8-fb5872c27be4","resolution":{"observed_at":"2026-05-17T04:58:10.254275Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.16720","last_updated":"2026-04-30T02:46:40Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-12-21T18:04:31Z","title":"OpenAI o1 System Card","version":2},"cited_work":{"arxiv_id":"2412.16720","doi":"10.48550/arxiv.2412.16720","metadata_source":"pith","pith_arxiv_id":"2412.16720","snapshot_observed_at":"2026-07-11T03:17:51.754565Z","title":"OpenAI o1 System Card","venue":"cs.AI","work_id":"68d3c334-0fc9-49e3-b7b0-a69afae933e2","year":2024},"citing_paper":{"arxiv_id":"2506.11763","last_updated":"2025-06-13T13:17:32Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-06-13T13:17:32Z","title":"DeepResearch Bench: A Comprehensive Benchmark for Deep Research Agents","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-05-16T08:07:39.384613Z"},"links":{"cited_paper":"/paper/2412.16720","citing_paper":"/paper/2506.11763"},"observation_digest":"sha256:cdb251863d02b6ddc0a713401299725960b7cf32e2a39ac5688725c821391d0c","observation_id":"1a1bb7b5-6d32-43c6-b028-34448807e9b3","resolution":{"observed_at":"2026-05-16T08:07:39.484125Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.16720","last_updated":"2026-04-30T02:46:40Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-12-21T18:04:31Z","title":"OpenAI o1 System Card","version":2},"cited_work":{"arxiv_id":"2412.16720","doi":"10.48550/arxiv.2412.16720","metadata_source":"pith","pith_arxiv_id":"2412.16720","snapshot_observed_at":"2026-07-11T03:17:51.754565Z","title":"OpenAI o1 System Card","venue":"cs.AI","work_id":"68d3c334-0fc9-49e3-b7b0-a69afae933e2","year":2024},"citing_paper":{"arxiv_id":"2506.13351","last_updated":"2026-05-07T20:19:13Z","snapshot_observed_at":"2026-07-31T17:48:52.945760Z","submitted_at":"2025-06-16T10:43:38Z","title":"Direct Reasoning Optimization: Token-Level Reasoning Reflectivity Meets Rubric Gates for Unverifiable Tasks","version":3},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-05-19T09:48:56.990745Z"},"links":{"cited_paper":"/paper/2412.16720","citing_paper":"/paper/2506.13351"},"observation_digest":"sha256:aeca3e4743d972f814f4f2cc0bfd6653f156245891d5e5acfe640542e69c1a6c","observation_id":"7202e720-1d9f-4df2-b612-4e6f98e094d0","resolution":{"observed_at":"2026-05-19T09:52:14.117083Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.16720","last_updated":"2026-04-30T02:46:40Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-12-21T18:04:31Z","title":"OpenAI o1 System Card","version":2},"cited_work":{"arxiv_id":"2412.16720","doi":"10.48550/arxiv.2412.16720","metadata_source":"pith","pith_arxiv_id":"2412.16720","snapshot_observed_at":"2026-07-11T03:17:51.754565Z","title":"OpenAI o1 System Card","venue":"cs.AI","work_id":"68d3c334-0fc9-49e3-b7b0-a69afae933e2","year":2024},"citing_paper":{"arxiv_id":"2506.13757","last_updated":"2025-11-05T23:46:20Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-06-16T17:58:50Z","title":"AutoVLA: A Vision-Language-Action Model for End-to-End Autonomous Driving with Adaptive Reasoning and Reinforcement Fine-Tuning","version":3},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-05-14T21:46:43.955825Z"},"links":{"cited_paper":"/paper/2412.16720","citing_paper":"/paper/2506.13757"},"observation_digest":"sha256:54e28dff9ee1af8a2c984b8c0dd2dfefb3cd4f94992b07a27a112cda7747b8f1","observation_id":"4aebf5fe-407e-4f3f-875b-02e86f2309e3","resolution":{"observed_at":"2026-05-14T21:46:44.239683Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.16720","last_updated":"2026-04-30T02:46:40Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-12-21T18:04:31Z","title":"OpenAI o1 System Card","version":2},"cited_work":{"arxiv_id":"2412.16720","doi":"10.48550/arxiv.2412.16720","metadata_source":"pith","pith_arxiv_id":"2412.16720","snapshot_observed_at":"2026-07-11T03:17:51.754565Z","title":"OpenAI o1 System Card","venue":"cs.AI","work_id":"68d3c334-0fc9-49e3-b7b0-a69afae933e2","year":2024},"citing_paper":{"arxiv_id":"2506.16796","last_updated":"2026-04-13T02:17:17Z","snapshot_observed_at":"2026-07-30T08:45:44.946546Z","submitted_at":"2025-06-20T07:21:21Z","title":"RealSR-R1: Reinforcement Learning for Real-World Image Super-Resolution with Vision-Language Chain-of-Thought","version":4},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-05-19T08:32:20.566798Z"},"links":{"cited_paper":"/paper/2412.16720","citing_paper":"/paper/2506.16796"},"observation_digest":"sha256:bf9b420c16f54d90e03d711dc118f8041b32c8357ab54ae514b703c858ec407f","observation_id":"43eee2ca-1ba7-42b1-8253-f44f0566c7ea","resolution":{"observed_at":"2026-05-19T08:33:02.171546Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.16720","last_updated":"2026-04-30T02:46:40Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-12-21T18:04:31Z","title":"OpenAI o1 System Card","version":2},"cited_work":{"arxiv_id":"2412.16720","doi":"10.48550/arxiv.2412.16720","metadata_source":"pith","pith_arxiv_id":"2412.16720","snapshot_observed_at":"2026-07-11T03:17:51.754565Z","title":"OpenAI o1 System Card","venue":"cs.AI","work_id":"68d3c334-0fc9-49e3-b7b0-a69afae933e2","year":2024},"citing_paper":{"arxiv_id":"2506.18871","last_updated":"2026-04-21T17:32:47Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-06-23T17:38:54Z","title":"OmniGen2: Towards Instruction-Aligned Multimodal Generation","version":4},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-05-19T07:47:34.464711Z"},"links":{"cited_paper":"/paper/2412.16720","citing_paper":"/paper/2506.18871"},"observation_digest":"sha256:3c35d07dfc853a77948bb7dbe5a02fd679bd473eed7c14be98f8378f239d01ab","observation_id":"4f53dc03-fe57-48f1-94b1-6ffcf0e6fefa","resolution":{"observed_at":"2026-05-19T07:52:10.852094Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.16720","last_updated":"2026-04-30T02:46:40Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-12-21T18:04:31Z","title":"OpenAI o1 System Card","version":2},"cited_work":{"arxiv_id":"2412.16720","doi":"10.48550/arxiv.2412.16720","metadata_source":"pith","pith_arxiv_id":"2412.16720","snapshot_observed_at":"2026-07-11T03:17:51.754565Z","title":"OpenAI o1 System Card","venue":"cs.AI","work_id":"68d3c334-0fc9-49e3-b7b0-a69afae933e2","year":2024},"citing_paper":{"arxiv_id":"2506.20670","last_updated":"2025-06-25T17:59:42Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-06-25T17:59:42Z","title":"MMSearch-R1: Incentivizing LMMs to Search","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-05-16T15:27:04.228144Z"},"links":{"cited_paper":"/paper/2412.16720","citing_paper":"/paper/2506.20670"},"observation_digest":"sha256:9ecb09f9b8b503972a4b4bb103c27115c6d7c9275dc01c648a34763602b4e216","observation_id":"253b989b-4dec-4533-bc0c-94017bd55637","resolution":{"observed_at":"2026-05-16T15:27:04.445309Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.16720","last_updated":"2026-04-30T02:46:40Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-12-21T18:04:31Z","title":"OpenAI o1 System Card","version":2},"cited_work":{"arxiv_id":"2412.16720","doi":"10.48550/arxiv.2412.16720","metadata_source":"pith","pith_arxiv_id":"2412.16720","snapshot_observed_at":"2026-07-11T03:17:51.754565Z","title":"OpenAI o1 System Card","venue":"cs.AI","work_id":"68d3c334-0fc9-49e3-b7b0-a69afae933e2","year":2024},"citing_paper":{"arxiv_id":"2506.22598","last_updated":"2026-04-21T20:17:15Z","snapshot_observed_at":"2026-08-03T23:13:09.503654Z","submitted_at":"2025-06-27T19:41:41Z","title":"RExBench: Can coding agents autonomously implement AI research extensions?","version":3},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-05-19T07:33:39.675929Z"},"links":{"cited_paper":"/paper/2412.16720","citing_paper":"/paper/2506.22598"},"observation_digest":"sha256:56d89b71476adb1a3333076c81b75fccf9c33081385511ba6437981b7cb6a277","observation_id":"32582b54-e9dd-4817-898e-2e7cbe13a2cc","resolution":{"observed_at":"2026-05-19T07:37:08.945052Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.16720","last_updated":"2026-04-30T02:46:40Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-12-21T18:04:31Z","title":"OpenAI o1 System Card","version":2},"cited_work":{"arxiv_id":"2412.16720","doi":"10.48550/arxiv.2412.16720","metadata_source":"pith","pith_arxiv_id":"2412.16720","snapshot_observed_at":"2026-07-11T03:17:51.754565Z","title":"OpenAI o1 System Card","venue":"cs.AI","work_id":"68d3c334-0fc9-49e3-b7b0-a69afae933e2","year":2024},"citing_paper":{"arxiv_id":"2507.00748","last_updated":"2026-04-12T11:20:16Z","snapshot_observed_at":"2026-07-31T10:24:51.553367Z","submitted_at":"2025-07-01T13:48:57Z","title":"Improving the Reasoning of Multi-Image Grounding in MLLMs via Reinforcement Learning","version":3},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-05-19T06:50:02.607136Z"},"links":{"cited_paper":"/paper/2412.16720","citing_paper":"/paper/2507.00748"},"observation_digest":"sha256:21c778181bc27df296241a6456e96bd1d8e0fddfcd296c53e68b9889d5c02a8b","observation_id":"0bb4ae82-075c-4828-8f71-bf0bb1f64881","resolution":{"observed_at":"2026-05-19T06:52:08.053692Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.16720","last_updated":"2026-04-30T02:46:40Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-12-21T18:04:31Z","title":"OpenAI o1 System Card","version":2},"cited_work":{"arxiv_id":"2412.16720","doi":"10.48550/arxiv.2412.16720","metadata_source":"pith","pith_arxiv_id":"2412.16720","snapshot_observed_at":"2026-07-11T03:17:51.754565Z","title":"OpenAI o1 System Card","venue":"cs.AI","work_id":"68d3c334-0fc9-49e3-b7b0-a69afae933e2","year":2024},"citing_paper":{"arxiv_id":"2507.01006","last_updated":"2026-01-01T13:07:25Z","snapshot_observed_at":"2026-08-03T18:50:30.558321Z","submitted_at":"2025-07-01T17:55:04Z","title":"GLM-4.5V and GLM-4.1V-Thinking: Towards Versatile Multimodal Reasoning with Scalable Reinforcement Learning","version":6},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-05-11T04:48:26.355351Z"},"links":{"cited_paper":"/paper/2412.16720","citing_paper":"/paper/2507.01006"},"observation_digest":"sha256:0477f6d4ec53add72151144bd78b650e68c0549f707e40e4fb008f3a6ad00d7b","observation_id":"9de0b98c-a221-4670-9e94-57be5e67862a","resolution":{"observed_at":"2026-05-11T04:48:26.835382Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.16720","last_updated":"2026-04-30T02:46:40Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-12-21T18:04:31Z","title":"OpenAI o1 System Card","version":2},"cited_work":{"arxiv_id":"2412.16720","doi":"10.48550/arxiv.2412.16720","metadata_source":"pith","pith_arxiv_id":"2412.16720","snapshot_observed_at":"2026-07-11T03:17:51.754565Z","title":"OpenAI o1 System Card","venue":"cs.AI","work_id":"68d3c334-0fc9-49e3-b7b0-a69afae933e2","year":2024},"citing_paper":{"arxiv_id":"2507.01679","last_updated":"2026-05-15T06:56:26Z","snapshot_observed_at":"2026-08-02T08:39:49.062624Z","submitted_at":"2025-07-02T13:04:09Z","title":"Blending Supervised and Reinforcement Fine-Tuning with Prefix Sampling","version":3},"reference_index":17,"source":"arxiv_source","source_observed_at":"2026-05-21T23:39:39.018498Z"},"links":{"cited_paper":"/paper/2412.16720","citing_paper":"/paper/2507.01679"},"observation_digest":"sha256:032cb9c49072d361ed7e3af1a19802a52553a1185abc33a31a620c8ee316516c","observation_id":"ae70cf07-b3f0-4b99-a193-7b2ce2ce82a4","resolution":{"observed_at":"2026-05-21T23:40:46.419287Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.16720","last_updated":"2026-04-30T02:46:40Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-12-21T18:04:31Z","title":"OpenAI o1 System Card","version":2},"cited_work":{"arxiv_id":"2412.16720","doi":"10.48550/arxiv.2412.16720","metadata_source":"pith","pith_arxiv_id":"2412.16720","snapshot_observed_at":"2026-07-11T03:17:51.754565Z","title":"OpenAI o1 System Card","venue":"cs.AI","work_id":"68d3c334-0fc9-49e3-b7b0-a69afae933e2","year":2024},"citing_paper":{"arxiv_id":"2507.01925","last_updated":"2025-07-02T17:34:52Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-07-02T17:34:52Z","title":"A Survey on Vision-Language-Action Models: An Action Tokenization Perspective","version":1},"reference_index":74,"source":"pdf_text","source_observed_at":"2026-05-17T14:08:34.893876Z"},"links":{"cited_paper":"/paper/2412.16720","citing_paper":"/paper/2507.01925"},"observation_digest":"sha256:d627d6e25c84c2790d6a86b6bb2312b3a00fcf055f7a311b5e9d6954825ec9b8","observation_id":"39a16f63-64d8-4043-a6e3-216d093d4a74","resolution":{"observed_at":"2026-05-17T14:08:35.258847Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.16720","last_updated":"2026-04-30T02:46:40Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-12-21T18:04:31Z","title":"OpenAI o1 System Card","version":2},"cited_work":{"arxiv_id":"2412.16720","doi":"10.48550/arxiv.2412.16720","metadata_source":"pith","pith_arxiv_id":"2412.16720","snapshot_observed_at":"2026-07-11T03:17:51.754565Z","title":"OpenAI o1 System Card","venue":"cs.AI","work_id":"68d3c334-0fc9-49e3-b7b0-a69afae933e2","year":2024},"citing_paper":{"arxiv_id":"2507.05920","last_updated":"2026-04-20T01:54:49Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-07-08T12:05:05Z","title":"High-Resolution Visual Reasoning via Multi-Turn Grounding-Based Reinforcement Learning","version":2},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-05-19T06:10:57.219445Z"},"links":{"cited_paper":"/paper/2412.16720","citing_paper":"/paper/2507.05920"},"observation_digest":"sha256:f25dc57b5268796c730513dcd3a48cb0f4b708c05920776f4d7b27b93c1382e8","observation_id":"f81de1b1-c5fb-4e6a-8362-81e7e1b1bbd0","resolution":{"observed_at":"2026-05-19T06:12:07.093722Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.16720","last_updated":"2026-04-30T02:46:40Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-12-21T18:04:31Z","title":"OpenAI o1 System Card","version":2},"cited_work":{"arxiv_id":"2412.16720","doi":"10.48550/arxiv.2412.16720","metadata_source":"pith","pith_arxiv_id":"2412.16720","snapshot_observed_at":"2026-07-11T03:17:51.754565Z","title":"OpenAI o1 System Card","venue":"cs.AI","work_id":"68d3c334-0fc9-49e3-b7b0-a69afae933e2","year":2024},"citing_paper":{"arxiv_id":"2507.12898","last_updated":"2025-12-20T02:16:12Z","snapshot_observed_at":"2026-07-30T09:36:32.113048Z","submitted_at":"2025-07-17T08:31:55Z","title":"Vidar: Embodied Video Diffusion Model for Generalist Manipulation","version":4},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-05-16T09:54:28.271928Z"},"links":{"cited_paper":"/paper/2412.16720","citing_paper":"/paper/2507.12898"},"observation_digest":"sha256:bc6549ff32228b358cd933ca3cde14c995bf8501d6755c859d2bf6c4046c6b9b","observation_id":"88838216-95ae-4596-b95d-66c9f3ded045","resolution":{"observed_at":"2026-05-16T09:54:28.310913Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.16720","last_updated":"2026-04-30T02:46:40Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-12-21T18:04:31Z","title":"OpenAI o1 System Card","version":2},"cited_work":{"arxiv_id":"2412.16720","doi":"10.48550/arxiv.2412.16720","metadata_source":"pith","pith_arxiv_id":"2412.16720","snapshot_observed_at":"2026-07-11T03:17:51.754565Z","title":"OpenAI o1 System Card","venue":"cs.AI","work_id":"68d3c334-0fc9-49e3-b7b0-a69afae933e2","year":2024},"citing_paper":{"arxiv_id":"2507.16307","last_updated":"2026-05-18T02:12:44Z","snapshot_observed_at":"2026-08-03T03:45:18.992655Z","submitted_at":"2025-07-22T07:48:32Z","title":"Perovskite-R1: a domain-specialized large language model for intelligent discovery of precursor additives and experimental design","version":2},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-05-22T00:26:35.977160Z"},"links":{"cited_paper":"/paper/2412.16720","citing_paper":"/paper/2507.16307"},"observation_digest":"sha256:be1dfe3e31c88e232479e43e998d02283bfe85972d26e28730fc8a2c58808004","observation_id":"c16d6205-5570-4a7f-82e3-38d54a5ea513","resolution":{"observed_at":"2026-05-22T00:30:49.261089Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.16720","last_updated":"2026-04-30T02:46:40Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-12-21T18:04:31Z","title":"OpenAI o1 System Card","version":2},"cited_work":{"arxiv_id":"2412.16720","doi":"10.48550/arxiv.2412.16720","metadata_source":"pith","pith_arxiv_id":"2412.16720","snapshot_observed_at":"2026-07-11T03:17:51.754565Z","title":"OpenAI o1 System Card","venue":"cs.AI","work_id":"68d3c334-0fc9-49e3-b7b0-a69afae933e2","year":2024},"citing_paper":{"arxiv_id":"2507.17746","last_updated":"2025-10-03T01:55:55Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-07-23T17:57:55Z","title":"Rubrics as Rewards: Reinforcement Learning Beyond Verifiable Domains","version":2},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-05-13T06:07:56.678339Z"},"links":{"cited_paper":"/paper/2412.16720","citing_paper":"/paper/2507.17746"},"observation_digest":"sha256:22caef4db629f37e9938934ad372668edfd0518a5003b7c6472683e5034b8609","observation_id":"a74a2886-1f1e-4555-9750-7ab6dabb193f","resolution":{"observed_at":"2026-05-13T06:07:56.771037Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.16720","last_updated":"2026-04-30T02:46:40Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-12-21T18:04:31Z","title":"OpenAI o1 System Card","version":2},"cited_work":{"arxiv_id":"2412.16720","doi":"10.48550/arxiv.2412.16720","metadata_source":"pith","pith_arxiv_id":"2412.16720","snapshot_observed_at":"2026-07-11T03:17:51.754565Z","title":"OpenAI o1 System Card","venue":"cs.AI","work_id":"68d3c334-0fc9-49e3-b7b0-a69afae933e2","year":2024},"citing_paper":{"arxiv_id":"2507.21433","last_updated":"2026-05-14T02:27:46Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-07-29T02:05:51Z","title":"ReasonCache: Accelerating Large Reasoning Model Serving through KV Cache Sharing","version":3},"reference_index":11,"source":"arxiv_source","source_observed_at":"2026-05-19T03:14:05.109011Z"},"links":{"cited_paper":"/paper/2412.16720","citing_paper":"/paper/2507.21433"},"observation_digest":"sha256:a903901cb9828996f08a279d512e45b08c64169c8dcf2c762fdf491047a1fd01","observation_id":"e08cda79-cec1-4f03-a7fa-ea03fdba05ff","resolution":{"observed_at":"2026-05-19T03:17:00.835326Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.16720","last_updated":"2026-04-30T02:46:40Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-12-21T18:04:31Z","title":"OpenAI o1 System Card","version":2},"cited_work":{"arxiv_id":"2412.16720","doi":"10.48550/arxiv.2412.16720","metadata_source":"pith","pith_arxiv_id":"2412.16720","snapshot_observed_at":"2026-07-11T03:17:51.754565Z","title":"OpenAI o1 System Card","venue":"cs.AI","work_id":"68d3c334-0fc9-49e3-b7b0-a69afae933e2","year":2024},"citing_paper":{"arxiv_id":"2507.21990","last_updated":"2026-04-14T13:50:18Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-07-29T16:40:49Z","title":"ChemDFM-R: A Chemical Reasoning LLM Enhanced with Atomized Chemical Knowledge","version":4},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-05-19T03:29:23.464348Z"},"links":{"cited_paper":"/paper/2412.16720","citing_paper":"/paper/2507.21990"},"observation_digest":"sha256:f115c8b2733f7db7b5511e64dcb99682dee3fc3b184a43d351178a8fd78d6016","observation_id":"3bcf737c-cdf7-4d54-bc35-b2e808f1bae1","resolution":{"observed_at":"2026-05-19T03:32:01.624288Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.16720","last_updated":"2026-04-30T02:46:40Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-12-21T18:04:31Z","title":"OpenAI o1 System Card","version":2},"cited_work":{"arxiv_id":"2412.16720","doi":"10.48550/arxiv.2412.16720","metadata_source":"pith","pith_arxiv_id":"2412.16720","snapshot_observed_at":"2026-07-11T03:17:51.754565Z","title":"OpenAI o1 System Card","venue":"cs.AI","work_id":"68d3c334-0fc9-49e3-b7b0-a69afae933e2","year":2024},"citing_paper":{"arxiv_id":"2508.01191","last_updated":"2026-05-08T20:20:58Z","snapshot_observed_at":"2026-07-06T22:06:38.785781Z","submitted_at":"2025-08-02T04:37:28Z","title":"Is Chain-of-Thought Reasoning of LLMs a Mirage? A Data Distribution Lens","version":6},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-05-19T01:18:31.661827Z"},"links":{"cited_paper":"/paper/2412.16720","citing_paper":"/paper/2508.01191"},"observation_digest":"sha256:3f0db505b33ea9566f757dbb5ed03ba3662748c1143c576cc818bdd737abec34","observation_id":"8ef82353-bb05-4bcc-b324-1b717f3a0643","resolution":{"observed_at":"2026-05-19T01:21:58.119945Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.16720","last_updated":"2026-04-30T02:46:40Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-12-21T18:04:31Z","title":"OpenAI o1 System Card","version":2},"cited_work":{"arxiv_id":"2412.16720","doi":"10.48550/arxiv.2412.16720","metadata_source":"pith","pith_arxiv_id":"2412.16720","snapshot_observed_at":"2026-07-11T03:17:51.754565Z","title":"OpenAI o1 System Card","venue":"cs.AI","work_id":"68d3c334-0fc9-49e3-b7b0-a69afae933e2","year":2024},"citing_paper":{"arxiv_id":"2508.06471","last_updated":"2025-08-08T17:21:06Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-08-08T17:21:06Z","title":"GLM-4.5: Agentic, Reasoning, and Coding (ARC) Foundation Models","version":1},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-05-11T17:50:08.399160Z"},"links":{"cited_paper":"/paper/2412.16720","citing_paper":"/paper/2508.06471"},"observation_digest":"sha256:ce1a323e11117ffa625d44ee1daf0dc6c247384fef5704b79a5441180848e21f","observation_id":"5397dd6e-baf0-4444-a03a-300edd956de5","resolution":{"observed_at":"2026-05-11T17:50:08.454947Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.16720","last_updated":"2026-04-30T02:46:40Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-12-21T18:04:31Z","title":"OpenAI o1 System Card","version":2},"cited_work":{"arxiv_id":"2412.16720","doi":"10.48550/arxiv.2412.16720","metadata_source":"pith","pith_arxiv_id":"2412.16720","snapshot_observed_at":"2026-07-11T03:17:51.754565Z","title":"OpenAI o1 System Card","venue":"cs.AI","work_id":"68d3c334-0fc9-49e3-b7b0-a69afae933e2","year":2024},"citing_paper":{"arxiv_id":"2508.07050","last_updated":"2026-04-22T03:08:54Z","snapshot_observed_at":"2026-07-06T22:10:31.258024Z","submitted_at":"2025-08-09T17:26:18Z","title":"ReasonRank: Empowering Passage Ranking with Strong Reasoning Ability","version":3},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-05-18T23:54:11.058239Z"},"links":{"cited_paper":"/paper/2412.16720","citing_paper":"/paper/2508.07050"},"observation_digest":"sha256:04c2d4d59af422c6dda48f6bd2b915ad52c9a09549642b6b2cf9001cae0501a4","observation_id":"d65a9e99-1f20-4bd4-81cb-3e3dd3250230","resolution":{"observed_at":"2026-05-18T23:56:55.119110Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.16720","last_updated":"2026-04-30T02:46:40Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-12-21T18:04:31Z","title":"OpenAI o1 System Card","version":2},"cited_work":{"arxiv_id":"2412.16720","doi":"10.48550/arxiv.2412.16720","metadata_source":"pith","pith_arxiv_id":"2412.16720","snapshot_observed_at":"2026-07-11T03:17:51.754565Z","title":"OpenAI o1 System Card","venue":"cs.AI","work_id":"68d3c334-0fc9-49e3-b7b0-a69afae933e2","year":2024},"citing_paper":{"arxiv_id":"2508.08574","last_updated":"2026-04-13T16:50:27Z","snapshot_observed_at":"2026-08-02T09:29:49.746608Z","submitted_at":"2025-08-12T02:19:15Z","title":"DeepFleet: Multi-Agent Foundation Models for Mobile Robots","version":3},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-05-19T00:13:27.533407Z"},"links":{"cited_paper":"/paper/2412.16720","citing_paper":"/paper/2508.08574"},"observation_digest":"sha256:bbccb34c60ef9e3ab294b0ebf8e645248a780fd7502d3680af4b2a13f93ac761","observation_id":"d452237d-7cff-4014-9d25-f7bca1163550","resolution":{"observed_at":"2026-05-19T00:16:55.436716Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.16720","last_updated":"2026-04-30T02:46:40Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-12-21T18:04:31Z","title":"OpenAI o1 System Card","version":2},"cited_work":{"arxiv_id":"2412.16720","doi":"10.48550/arxiv.2412.16720","metadata_source":"pith","pith_arxiv_id":"2412.16720","snapshot_observed_at":"2026-07-11T03:17:51.754565Z","title":"OpenAI o1 System Card","venue":"cs.AI","work_id":"68d3c334-0fc9-49e3-b7b0-a69afae933e2","year":2024},"citing_paper":{"arxiv_id":"2508.08636","last_updated":"2026-05-20T08:06:05Z","snapshot_observed_at":"2026-08-04T03:35:42.053775Z","submitted_at":"2025-08-12T05:00:00Z","title":"InternBootcamp Technical Report: Boosting LLM Reasoning with Verifiable Task Scaling","version":2},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-05-21T22:33:09.674822Z"},"links":{"cited_paper":"/paper/2412.16720","citing_paper":"/paper/2508.08636"},"observation_digest":"sha256:de93960b8ef91d4b5a6d3a02af3acc1719c73c5562fef7c4cb8570a4f403e599","observation_id":"de10f4ef-7c99-499e-873b-e61f459d1f80","resolution":{"observed_at":"2026-05-21T22:34:24.030159Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.16720","last_updated":"2026-04-30T02:46:40Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-12-21T18:04:31Z","title":"OpenAI o1 System Card","version":2},"cited_work":{"arxiv_id":"2412.16720","doi":"10.48550/arxiv.2412.16720","metadata_source":"pith","pith_arxiv_id":"2412.16720","snapshot_observed_at":"2026-07-11T03:17:51.754565Z","title":"OpenAI o1 System Card","venue":"cs.AI","work_id":"68d3c334-0fc9-49e3-b7b0-a69afae933e2","year":2024},"citing_paper":{"arxiv_id":"2508.10164","last_updated":"2026-04-15T15:39:48Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-08-13T20:00:09Z","title":"Pruning Long Chain-of-Thought of Large Reasoning Models via Small-Scale Preference Optimization","version":2},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-05-18T22:26:52.748349Z"},"links":{"cited_paper":"/paper/2412.16720","citing_paper":"/paper/2508.10164"},"observation_digest":"sha256:af3eef1765cd6a035984c2d1486e70422ba92a87f6b875edd551d7997e11b4b2","observation_id":"19da6661-8271-4c86-94b5-4274b5fd6bf2","resolution":{"observed_at":"2026-05-18T22:31:53.137647Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.16720","last_updated":"2026-04-30T02:46:40Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-12-21T18:04:31Z","title":"OpenAI o1 System Card","version":2},"cited_work":{"arxiv_id":"2412.16720","doi":"10.48550/arxiv.2412.16720","metadata_source":"pith","pith_arxiv_id":"2412.16720","snapshot_observed_at":"2026-07-11T03:17:51.754565Z","title":"OpenAI o1 System Card","venue":"cs.AI","work_id":"68d3c334-0fc9-49e3-b7b0-a69afae933e2","year":2024},"citing_paper":{"arxiv_id":"2508.10177","last_updated":"2026-04-22T18:28:23Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-08-13T20:29:56Z","title":"KompeteAI: Accelerated Autonomous Multi-Agent System for End-to-End Pipeline Generation for Machine Learning Problems","version":3},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-05-18T22:22:19.478156Z"},"links":{"cited_paper":"/paper/2412.16720","citing_paper":"/paper/2508.10177"},"observation_digest":"sha256:fe7fc8260f9047679ce9e8ed00280bda88fd5c98fdaf4fab0b520661f4dd4d15","observation_id":"544c7e5b-4bc4-4ba1-b6eb-5ee0db9e0164","resolution":{"observed_at":"2026-05-18T22:22:51.746133Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.16720","last_updated":"2026-04-30T02:46:40Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-12-21T18:04:31Z","title":"OpenAI o1 System Card","version":2},"cited_work":{"arxiv_id":"2412.16720","doi":"10.48550/arxiv.2412.16720","metadata_source":"pith","pith_arxiv_id":"2412.16720","snapshot_observed_at":"2026-07-11T03:17:51.754565Z","title":"OpenAI o1 System Card","venue":"cs.AI","work_id":"68d3c334-0fc9-49e3-b7b0-a69afae933e2","year":2024},"citing_paper":{"arxiv_id":"2508.11196","last_updated":"2026-05-06T08:41:14Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-08-15T04:06:40Z","title":"UAV-VL-R1: Generalizing Vision-Language Models via Supervised Fine-Tuning and Multi-Stage GRPO for UAV Visual Reasoning","version":2},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-05-18T22:17:41.758059Z"},"links":{"cited_paper":"/paper/2412.16720","citing_paper":"/paper/2508.11196"},"observation_digest":"sha256:99f480b59e189d5e36e1a171e51cf82846b6be388887e24e6ca74ef2e164bb16","observation_id":"b4d63219-35ec-41a7-8792-ce42ec845419","resolution":{"observed_at":"2026-05-18T22:21:53.299878Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.16720","last_updated":"2026-04-30T02:46:40Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-12-21T18:04:31Z","title":"OpenAI o1 System Card","version":2},"cited_work":{"arxiv_id":"2412.16720","doi":"10.48550/arxiv.2412.16720","metadata_source":"pith","pith_arxiv_id":"2412.16720","snapshot_observed_at":"2026-07-11T03:17:51.754565Z","title":"OpenAI o1 System Card","venue":"cs.AI","work_id":"68d3c334-0fc9-49e3-b7b0-a69afae933e2","year":2024},"citing_paper":{"arxiv_id":"2508.11222","last_updated":"2025-12-05T05:36:55Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-08-15T05:03:26Z","title":"ORFuzz: Fuzzing the \"Other Side\" of LLM Safety -- Testing Over-Refusal","version":2},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-05-18T23:27:52.438709Z"},"links":{"cited_paper":"/paper/2412.16720","citing_paper":"/paper/2508.11222"},"observation_digest":"sha256:ba8ca91493cd55a05e533cbab1b9940ca76291f80ffccbc4c8aa826c0bab294d","observation_id":"913b3b50-b0c9-430b-8d4b-7ce70d753802","resolution":{"observed_at":"2026-05-18T23:31:54.486170Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.16720","last_updated":"2026-04-30T02:46:40Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-12-21T18:04:31Z","title":"OpenAI o1 System Card","version":2},"cited_work":{"arxiv_id":"2412.16720","doi":"10.48550/arxiv.2412.16720","metadata_source":"pith","pith_arxiv_id":"2412.16720","snapshot_observed_at":"2026-07-11T03:17:51.754565Z","title":"OpenAI o1 System Card","venue":"cs.AI","work_id":"68d3c334-0fc9-49e3-b7b0-a69afae933e2","year":2024},"citing_paper":{"arxiv_id":"2508.13073","last_updated":"2025-09-01T08:10:01Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-08-18T16:45:48Z","title":"Large VLM-based Vision-Language-Action Models for Robotic Manipulation: A Survey","version":2},"reference_index":180,"source":"pdf_text","source_observed_at":"2026-05-17T20:28:15.818016Z"},"links":{"cited_paper":"/paper/2412.16720","citing_paper":"/paper/2508.13073"},"observation_digest":"sha256:b896e2c972fe42871808939d59d59145b320895c1516bcbeb35ea2ae2f1fc192","observation_id":"17bfb0e5-8462-4dd7-b66b-dee8c5afb3fb","resolution":{"observed_at":"2026-05-17T20:28:16.122827Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.16720","last_updated":"2026-04-30T02:46:40Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-12-21T18:04:31Z","title":"OpenAI o1 System Card","version":2},"cited_work":{"arxiv_id":"2412.16720","doi":"10.48550/arxiv.2412.16720","metadata_source":"pith","pith_arxiv_id":"2412.16720","snapshot_observed_at":"2026-07-11T03:17:51.754565Z","title":"OpenAI o1 System Card","venue":"cs.AI","work_id":"68d3c334-0fc9-49e3-b7b0-a69afae933e2","year":2024},"citing_paper":{"arxiv_id":"2508.13755","last_updated":"2026-04-12T13:17:04Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-08-19T11:51:40Z","title":"Depth-Breadth Synergy in RLVR: Unlocking LLM Reasoning Gains with Adaptive Exploration","version":8},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-05-18T22:33:01.074518Z"},"links":{"cited_paper":"/paper/2412.16720","citing_paper":"/paper/2508.13755"},"observation_digest":"sha256:0db4f2b4f21a7738d08602630cfe8baa87e36baf294b5c95ac0839c8d6520d54","observation_id":"6f1af644-653e-4110-89fe-736ba973034a","resolution":{"observed_at":"2026-05-18T22:36:53.695805Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.16720","last_updated":"2026-04-30T02:46:40Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-12-21T18:04:31Z","title":"OpenAI o1 System Card","version":2},"cited_work":{"arxiv_id":"2412.16720","doi":"10.48550/arxiv.2412.16720","metadata_source":"pith","pith_arxiv_id":"2412.16720","snapshot_observed_at":"2026-07-11T03:17:51.754565Z","title":"OpenAI o1 System Card","venue":"cs.AI","work_id":"68d3c334-0fc9-49e3-b7b0-a69afae933e2","year":2024},"citing_paper":{"arxiv_id":"2508.13998","last_updated":"2026-04-06T03:29:44Z","snapshot_observed_at":"2026-08-03T11:31:47.613184Z","submitted_at":"2025-08-19T16:50:01Z","title":"Embodied-R1: Reinforced Embodied Reasoning for General Robotic Manipulation","version":2},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-05-18T22:04:34.235731Z"},"links":{"cited_paper":"/paper/2412.16720","citing_paper":"/paper/2508.13998"},"observation_digest":"sha256:071f6eaa8fa020e65daf4630d88491f97ef86b07f42660a6057e883faefab2c9","observation_id":"5ed0798b-86a1-41d3-bc2d-bb36fb6dc384","resolution":{"observed_at":"2026-05-18T22:06:51.683164Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.16720","last_updated":"2026-04-30T02:46:40Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-12-21T18:04:31Z","title":"OpenAI o1 System Card","version":2},"cited_work":{"arxiv_id":"2412.16720","doi":"10.48550/arxiv.2412.16720","metadata_source":"pith","pith_arxiv_id":"2412.16720","snapshot_observed_at":"2026-07-11T03:17:51.754565Z","title":"OpenAI o1 System Card","venue":"cs.AI","work_id":"68d3c334-0fc9-49e3-b7b0-a69afae933e2","year":2024},"citing_paper":{"arxiv_id":"2508.15487","last_updated":"2025-08-21T12:09:58Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-08-21T12:09:58Z","title":"Dream 7B: Diffusion Large Language Models","version":1},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-05-11T16:25:53.143469Z"},"links":{"cited_paper":"/paper/2412.16720","citing_paper":"/paper/2508.15487"},"observation_digest":"sha256:bc2b61906001603c913d3c8628422df26d35230f5bdeca8dae4d10999fab3f92","observation_id":"7a1a3da7-285a-4fbc-bcd6-d2dc22a410b6","resolution":{"observed_at":"2026-05-11T16:25:53.476360Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.16720","last_updated":"2026-04-30T02:46:40Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-12-21T18:04:31Z","title":"OpenAI o1 System Card","version":2},"cited_work":{"arxiv_id":"2412.16720","doi":"10.48550/arxiv.2412.16720","metadata_source":"pith","pith_arxiv_id":"2412.16720","snapshot_observed_at":"2026-07-11T03:17:51.754565Z","title":"OpenAI o1 System Card","venue":"cs.AI","work_id":"68d3c334-0fc9-49e3-b7b0-a69afae933e2","year":2024},"citing_paper":{"arxiv_id":"2508.16165","last_updated":"2026-04-10T08:22:26Z","snapshot_observed_at":"2026-07-06T22:16:34.442202Z","submitted_at":"2025-08-22T07:38:37Z","title":"Investigating Multimodal Large Language Models to Support Usability Evaluation","version":2},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-05-18T22:04:19.716428Z"},"links":{"cited_paper":"/paper/2412.16720","citing_paper":"/paper/2508.16165"},"observation_digest":"sha256:ba892a92608158df12b3db14d4b6b2b7d2c8dbc35f5a4770d546840d172ca50b","observation_id":"ff9fd392-d94b-4947-a68d-6c6262664d1b","resolution":{"observed_at":"2026-05-18T22:06:51.845586Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.16720","last_updated":"2026-04-30T02:46:40Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-12-21T18:04:31Z","title":"OpenAI o1 System Card","version":2},"cited_work":{"arxiv_id":"2412.16720","doi":"10.48550/arxiv.2412.16720","metadata_source":"pith","pith_arxiv_id":"2412.16720","snapshot_observed_at":"2026-07-11T03:17:51.754565Z","title":"OpenAI o1 System Card","venue":"cs.AI","work_id":"68d3c334-0fc9-49e3-b7b0-a69afae933e2","year":2024},"citing_paper":{"arxiv_id":"2508.20697","last_updated":"2026-05-09T10:15:42Z","snapshot_observed_at":"2026-08-03T11:14:46.347235Z","submitted_at":"2025-08-28T12:07:11Z","title":"Token Buncher: Shielding LLMs from Harmful Reinforcement Learning Fine-Tuning","version":3},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-05-18T20:40:44.496392Z"},"links":{"cited_paper":"/paper/2412.16720","citing_paper":"/paper/2508.20697"},"observation_digest":"sha256:2cf6834f7aa7c75bf974932bf41f0e80591fcbff390766598f3a04050c41f4ce","observation_id":"24d87b2b-060f-42af-b52c-3c5217a6942b","resolution":{"observed_at":"2026-05-18T20:41:50.471169Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.16720","last_updated":"2026-04-30T02:46:40Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-12-21T18:04:31Z","title":"OpenAI o1 System Card","version":2},"cited_work":{"arxiv_id":"2412.16720","doi":"10.48550/arxiv.2412.16720","metadata_source":"pith","pith_arxiv_id":"2412.16720","snapshot_observed_at":"2026-07-11T03:17:51.754565Z","title":"OpenAI o1 System Card","venue":"cs.AI","work_id":"68d3c334-0fc9-49e3-b7b0-a69afae933e2","year":2024},"citing_paper":{"arxiv_id":"2509.02544","last_updated":"2025-09-05T14:59:27Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-09-02T17:44:45Z","title":"UI-TARS-2 Technical Report: Advancing GUI Agent with Multi-Turn Reinforcement Learning","version":2},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-05-13T10:13:58.774968Z"},"links":{"cited_paper":"/paper/2412.16720","citing_paper":"/paper/2509.02544"},"observation_digest":"sha256:9a810b42973a94840d7059435b7cd7c700d1339ac63c38db25091e4a1ddf84d4","observation_id":"2fccd53a-de22-41b0-ac7e-6d0151c13033","resolution":{"observed_at":"2026-05-13T10:13:58.886621Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.16720","last_updated":"2026-04-30T02:46:40Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-12-21T18:04:31Z","title":"OpenAI o1 System Card","version":2},"cited_work":{"arxiv_id":"2412.16720","doi":"10.48550/arxiv.2412.16720","metadata_source":"pith","pith_arxiv_id":"2412.16720","snapshot_observed_at":"2026-07-11T03:17:51.754565Z","title":"OpenAI o1 System Card","venue":"cs.AI","work_id":"68d3c334-0fc9-49e3-b7b0-a69afae933e2","year":2024},"citing_paper":{"arxiv_id":"2509.02547","last_updated":"2026-04-17T18:09:08Z","snapshot_observed_at":"2026-08-03T09:07:42.489237Z","submitted_at":"2025-09-02T17:46:26Z","title":"The Landscape of Agentic Reinforcement Learning for LLMs: A Survey","version":5},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-05-18T19:19:36.427337Z"},"links":{"cited_paper":"/paper/2412.16720","citing_paper":"/paper/2509.02547"},"observation_digest":"sha256:a0aea0b690fb463b3a0c4292d57982d65ff1deb7a7921d894364abf59fb717d1","observation_id":"2c337282-0282-4e35-b81b-aebb6370eff7","resolution":{"observed_at":"2026-05-18T19:21:48.266422Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.16720","last_updated":"2026-04-30T02:46:40Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-12-21T18:04:31Z","title":"OpenAI o1 System Card","version":2},"cited_work":{"arxiv_id":"2412.16720","doi":"10.48550/arxiv.2412.16720","metadata_source":"pith","pith_arxiv_id":"2412.16720","snapshot_observed_at":"2026-07-11T03:17:51.754565Z","title":"OpenAI o1 System Card","venue":"cs.AI","work_id":"68d3c334-0fc9-49e3-b7b0-a69afae933e2","year":2024},"citing_paper":{"arxiv_id":"2509.03403","last_updated":"2026-05-15T21:29:46Z","snapshot_observed_at":"2026-07-06T22:23:00.681940Z","submitted_at":"2025-09-03T15:28:51Z","title":"Beyond Correctness: Harmonizing Process and Outcome Rewards through RL Training","version":2},"reference_index":12,"source":"arxiv_source","source_observed_at":"2026-05-21T22:38:57.833414Z"},"links":{"cited_paper":"/paper/2412.16720","citing_paper":"/paper/2509.03403"},"observation_digest":"sha256:b883841169bb0abe24061c2e3f53e9bb9f5a3b6a84697119f8d6a6d5e2a41846","observation_id":"a0607676-f445-47a1-98e5-a0641d2c447d","resolution":{"observed_at":"2026-05-21T22:40:43.248068Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.16720","last_updated":"2026-04-30T02:46:40Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-12-21T18:04:31Z","title":"OpenAI o1 System Card","version":2},"cited_work":{"arxiv_id":"2412.16720","doi":"10.48550/arxiv.2412.16720","metadata_source":"pith","pith_arxiv_id":"2412.16720","snapshot_observed_at":"2026-07-11T03:17:51.754565Z","title":"OpenAI o1 System Card","venue":"cs.AI","work_id":"68d3c334-0fc9-49e3-b7b0-a69afae933e2","year":2024},"citing_paper":{"arxiv_id":"2509.05489","last_updated":"2026-04-16T20:13:16Z","snapshot_observed_at":"2026-07-06T22:24:51.648354Z","submitted_at":"2025-09-05T20:39:43Z","title":"Self-Aligned Reward: Towards Effective and Efficient Reasoners","version":2},"reference_index":19,"source":"arxiv_source","source_observed_at":"2026-05-18T18:27:23.076544Z"},"links":{"cited_paper":"/paper/2412.16720","citing_paper":"/paper/2509.05489"},"observation_digest":"sha256:f6dc06da83c337b51052388d6d9a9a6e42352b867e7895e997d57666ec46b537","observation_id":"83a4d0c5-cfa6-4a61-85c3-0105b51c4cb1","resolution":{"observed_at":"2026-05-18T18:31:44.594336Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.16720","last_updated":"2026-04-30T02:46:40Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-12-21T18:04:31Z","title":"OpenAI o1 System Card","version":2},"cited_work":{"arxiv_id":"2412.16720","doi":"10.48550/arxiv.2412.16720","metadata_source":"pith","pith_arxiv_id":"2412.16720","snapshot_observed_at":"2026-07-11T03:17:51.754565Z","title":"OpenAI o1 System Card","venue":"cs.AI","work_id":"68d3c334-0fc9-49e3-b7b0-a69afae933e2","year":2024},"citing_paper":{"arxiv_id":"2509.08016","last_updated":"2026-04-09T01:22:20Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-09-09T00:55:04Z","title":"Video Parallel Scaling: Aggregating Diverse Frame Subsets for VideoLLMs","version":2},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-05-18T18:35:01.328250Z"},"links":{"cited_paper":"/paper/2412.16720","citing_paper":"/paper/2509.08016"},"observation_digest":"sha256:0f9d2e55634c282c6da8c655ad4e92a028d18dd19829c71087b9a67b4af331ff","observation_id":"d6a8b995-12b9-4a65-9e70-e7ed2e0c7689","resolution":{"observed_at":"2026-05-18T18:36:44.205224Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.16720","last_updated":"2026-04-30T02:46:40Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-12-21T18:04:31Z","title":"OpenAI o1 System Card","version":2},"cited_work":{"arxiv_id":"2412.16720","doi":"10.48550/arxiv.2412.16720","metadata_source":"pith","pith_arxiv_id":"2412.16720","snapshot_observed_at":"2026-07-11T03:17:51.754565Z","title":"OpenAI o1 System Card","venue":"cs.AI","work_id":"68d3c334-0fc9-49e3-b7b0-a69afae933e2","year":2024},"citing_paper":{"arxiv_id":"2509.08827","last_updated":"2025-10-09T17:08:52Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-09-10T17:59:43Z","title":"A Survey of Reinforcement Learning for Large Reasoning Models","version":3},"reference_index":227,"source":"arxiv_source","source_observed_at":"2026-05-18T00:02:24.352947Z"},"links":{"cited_paper":"/paper/2412.16720","citing_paper":"/paper/2509.08827"},"observation_digest":"sha256:bff7685be6f13976d7468ea1c98ae2a9c9a541c26aa5d42942a07ac68234a13e","observation_id":"1f625a40-1562-4379-b754-7f6c3b0239fd","resolution":{"observed_at":"2026-05-18T00:02:24.504028Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.16720","last_updated":"2026-04-30T02:46:40Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-12-21T18:04:31Z","title":"OpenAI o1 System Card","version":2},"cited_work":{"arxiv_id":"2412.16720","doi":"10.48550/arxiv.2412.16720","metadata_source":"pith","pith_arxiv_id":"2412.16720","snapshot_observed_at":"2026-07-11T03:17:51.754565Z","title":"OpenAI o1 System Card","venue":"cs.AI","work_id":"68d3c334-0fc9-49e3-b7b0-a69afae933e2","year":2024},"citing_paper":{"arxiv_id":"2509.09674","last_updated":"2025-09-11T17:59:17Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-09-11T17:59:17Z","title":"SimpleVLA-RL: Scaling VLA Training via Reinforcement Learning","version":1},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-05-15T08:02:11.189795Z"},"links":{"cited_paper":"/paper/2412.16720","citing_paper":"/paper/2509.09674"},"observation_digest":"sha256:15f3e3c274a5e1e19c11433e4407bbdfb69fd8e1f55d32b2073384f6ed2198b1","observation_id":"98320af2-3cb3-40c0-9400-f30b76b54d2d","resolution":{"observed_at":"2026-05-15T08:02:11.416354Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.16720","last_updated":"2026-04-30T02:46:40Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-12-21T18:04:31Z","title":"OpenAI o1 System Card","version":2},"cited_work":{"arxiv_id":"2412.16720","doi":"10.48550/arxiv.2412.16720","metadata_source":"pith","pith_arxiv_id":"2412.16720","snapshot_observed_at":"2026-07-11T03:17:51.754565Z","title":"OpenAI o1 System Card","venue":"cs.AI","work_id":"68d3c334-0fc9-49e3-b7b0-a69afae933e2","year":2024},"citing_paper":{"arxiv_id":"2509.10546","last_updated":"2026-04-24T18:29:01Z","snapshot_observed_at":"2026-08-02T04:58:06.974646Z","submitted_at":"2025-09-07T22:35:15Z","title":"Learning to Conceal Risk: Controllable Multi-turn Red Teaming for LLMs in the Financial Domain","version":2},"reference_index":14,"source":"arxiv_source","source_observed_at":"2026-05-18T17:49:42.112564Z"},"links":{"cited_paper":"/paper/2412.16720","citing_paper":"/paper/2509.10546"},"observation_digest":"sha256:94be638001c892161d15e14ee4d62ef4aef62fe6f5c07b63cb962f4c20c6801e","observation_id":"574447e6-580c-4ffb-ac55-58904c5720bc","resolution":{"observed_at":"2026-05-18T17:51:41.971828Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.16720","last_updated":"2026-04-30T02:46:40Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-12-21T18:04:31Z","title":"OpenAI o1 System Card","version":2},"cited_work":{"arxiv_id":"2412.16720","doi":"10.48550/arxiv.2412.16720","metadata_source":"pith","pith_arxiv_id":"2412.16720","snapshot_observed_at":"2026-07-11T03:17:51.754565Z","title":"OpenAI o1 System Card","venue":"cs.AI","work_id":"68d3c334-0fc9-49e3-b7b0-a69afae933e2","year":2024},"citing_paper":{"arxiv_id":"2509.11206","last_updated":"2026-04-20T05:43:30Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-09-14T10:24:13Z","title":"Evalet: Evaluating Large Language Models through Functional Fragmentation","version":4},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-05-18T16:57:25.259866Z"},"links":{"cited_paper":"/paper/2412.16720","citing_paper":"/paper/2509.11206"},"observation_digest":"sha256:c6b5b2b61c41bffb4b54a8f3fdbca78866e33590824d744d29e4c943056f6759","observation_id":"db7ec883-0796-408a-ba92-1aa209807630","resolution":{"observed_at":"2026-05-18T17:01:40.077741Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.16720","last_updated":"2026-04-30T02:46:40Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-12-21T18:04:31Z","title":"OpenAI o1 System Card","version":2},"cited_work":{"arxiv_id":"2412.16720","doi":"10.48550/arxiv.2412.16720","metadata_source":"pith","pith_arxiv_id":"2412.16720","snapshot_observed_at":"2026-07-11T03:17:51.754565Z","title":"OpenAI o1 System Card","venue":"cs.AI","work_id":"68d3c334-0fc9-49e3-b7b0-a69afae933e2","year":2024},"citing_paper":{"arxiv_id":"2509.19349","last_updated":"2025-09-17T17:49:02Z","snapshot_observed_at":"2026-08-04T07:22:23.455386Z","submitted_at":"2025-09-17T17:49:02Z","title":"ShinkaEvolve: Towards Open-Ended And Sample-Efficient Program Evolution","version":1},"reference_index":131,"source":"arxiv_source","source_observed_at":"2026-05-16T13:58:58.627748Z"},"links":{"cited_paper":"/paper/2412.16720","citing_paper":"/paper/2509.19349"},"observation_digest":"sha256:5c5c60b29da9c719db94710426d243011c9bb39f5082af8b6c25deb610db0da1","observation_id":"808553af-efbe-4e01-b0e9-875ff5273824","resolution":{"observed_at":"2026-05-16T13:58:58.904823Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.16720","last_updated":"2026-04-30T02:46:40Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-12-21T18:04:31Z","title":"OpenAI o1 System Card","version":2},"cited_work":{"arxiv_id":"2412.16720","doi":"10.48550/arxiv.2412.16720","metadata_source":"pith","pith_arxiv_id":"2412.16720","snapshot_observed_at":"2026-07-11T03:17:51.754565Z","title":"OpenAI o1 System Card","venue":"cs.AI","work_id":"68d3c334-0fc9-49e3-b7b0-a69afae933e2","year":2024},"citing_paper":{"arxiv_id":"2509.20328","last_updated":"2025-09-29T20:44:46Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-09-24T17:17:27Z","title":"Video models are zero-shot learners and reasoners","version":2},"reference_index":75,"source":"pdf_text","source_observed_at":"2026-05-14T02:16:45.554252Z"},"links":{"cited_paper":"/paper/2412.16720","citing_paper":"/paper/2509.20328"},"observation_digest":"sha256:de604c15ac51ac885d1e5ad1bbe18cee13a4e6e0007727d5bcd6fdd34fc58781","observation_id":"5bd3cd9d-904f-446a-a968-c1c1e5f1c99e","resolution":{"observed_at":"2026-05-14T02:16:45.711478Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.16720","last_updated":"2026-04-30T02:46:40Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-12-21T18:04:31Z","title":"OpenAI o1 System Card","version":2},"cited_work":{"arxiv_id":"2412.16720","doi":"10.48550/arxiv.2412.16720","metadata_source":"pith","pith_arxiv_id":"2412.16720","snapshot_observed_at":"2026-07-11T03:17:51.754565Z","title":"OpenAI o1 System Card","venue":"cs.AI","work_id":"68d3c334-0fc9-49e3-b7b0-a69afae933e2","year":2024},"citing_paper":{"arxiv_id":"2509.21623","last_updated":"2026-04-16T21:29:54Z","snapshot_observed_at":"2026-08-03T21:57:13.209890Z","submitted_at":"2025-09-25T21:42:27Z","title":"OjaKV: Context-Aware Online Low-Rank KV Cache Compression","version":2},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-05-18T13:26:02.980973Z"},"links":{"cited_paper":"/paper/2412.16720","citing_paper":"/paper/2509.21623"},"observation_digest":"sha256:0925b543b8ed15c7e8604082c3b243ac792ab58ecca6e15ddfd0e8e17ce394ea","observation_id":"b6c96277-da22-471b-bf00-77d67fc3af61","resolution":{"observed_at":"2026-05-18T13:26:24.752396Z","resolver_source":"local_arxiv","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.16720","last_updated":"2026-04-30T02:46:40Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-12-21T18:04:31Z","title":"OpenAI o1 System Card","version":2},"cited_work":{"arxiv_id":"2412.16720","doi":"10.48550/arxiv.2412.16720","metadata_source":"pith","pith_arxiv_id":"2412.16720","snapshot_observed_at":"2026-07-11T03:17:51.754565Z","title":"OpenAI o1 System Card","venue":"cs.AI","work_id":"68d3c334-0fc9-49e3-b7b0-a69afae933e2","year":2024},"citing_paper":{"arxiv_id":"2509.21743","last_updated":"2026-03-31T22:32:08Z","snapshot_observed_at":"2026-07-06T22:30:50.642382Z","submitted_at":"2025-09-26T01:17:35Z","title":"Retrieval-of-Thought: Efficient Reasoning via Reusing Thoughts","version":2},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-05-18T13:42:07.883909Z"},"links":{"cited_paper":"/paper/2412.16720","citing_paper":"/paper/2509.21743"},"observation_digest":"sha256:d4e891c25204deb27a8103dfb012514663860014de58074613174b05866903b1","observation_id":"ea2f2da2-8324-45d8-95d7-2949ec9cf640","resolution":{"observed_at":"2026-05-18T13:42:38.671584Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.16720","last_updated":"2026-04-30T02:46:40Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-12-21T18:04:31Z","title":"OpenAI o1 System Card","version":2},"cited_work":{"arxiv_id":"2412.16720","doi":"10.48550/arxiv.2412.16720","metadata_source":"pith","pith_arxiv_id":"2412.16720","snapshot_observed_at":"2026-07-11T03:17:51.754565Z","title":"OpenAI o1 System Card","venue":"cs.AI","work_id":"68d3c334-0fc9-49e3-b7b0-a69afae933e2","year":2024},"citing_paper":{"arxiv_id":"2509.21976","last_updated":"2026-04-23T16:06:02Z","snapshot_observed_at":"2026-08-02T20:20:43.339546Z","submitted_at":"2025-09-26T07:01:12Z","title":"Geo-R1: Improving Few-Shot Geospatial Referring Expression Understanding with Reinforcement Fine-Tuning","version":3},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-05-18T14:09:13.310620Z"},"links":{"cited_paper":"/paper/2412.16720","citing_paper":"/paper/2509.21976"},"observation_digest":"sha256:a0a26afa8ac3188bcbdc4b80628fc43831177d0693922659628761ab77f2c971","observation_id":"5fc32b05-4502-4133-ac63-8010fc9d2791","resolution":{"observed_at":"2026-05-18T14:11:27.554766Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.16720","last_updated":"2026-04-30T02:46:40Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-12-21T18:04:31Z","title":"OpenAI o1 System Card","version":2},"cited_work":{"arxiv_id":"2412.16720","doi":"10.48550/arxiv.2412.16720","metadata_source":"pith","pith_arxiv_id":"2412.16720","snapshot_observed_at":"2026-07-11T03:17:51.754565Z","title":"OpenAI o1 System Card","venue":"cs.AI","work_id":"68d3c334-0fc9-49e3-b7b0-a69afae933e2","year":2024},"citing_paper":{"arxiv_id":"2509.23322","last_updated":"2026-04-09T10:37:26Z","snapshot_observed_at":"2026-08-02T12:34:37.611019Z","submitted_at":"2025-09-27T14:13:41Z","title":"Mitigating Visual Context Degradation in Large Multimodal Models: A Training-Free Decoupled Agentic Framework","version":2},"reference_index":21,"source":"arxiv_source","source_observed_at":"2026-05-18T12:31:25.257879Z"},"links":{"cited_paper":"/paper/2412.16720","citing_paper":"/paper/2509.23322"},"observation_digest":"sha256:62e77cf0eb5a28c1a47d8529991fc48e04f79ff37b59085e744fa22d09a4290a","observation_id":"87ffe0e7-8f66-42b3-b0fc-a10df1cc34be","resolution":{"observed_at":"2026-05-18T12:32:36.444003Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.16720","last_updated":"2026-04-30T02:46:40Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-12-21T18:04:31Z","title":"OpenAI o1 System Card","version":2},"cited_work":{"arxiv_id":"2412.16720","doi":"10.48550/arxiv.2412.16720","metadata_source":"pith","pith_arxiv_id":"2412.16720","snapshot_observed_at":"2026-07-11T03:17:51.754565Z","title":"OpenAI o1 System Card","venue":"cs.AI","work_id":"68d3c334-0fc9-49e3-b7b0-a69afae933e2","year":2024},"citing_paper":{"arxiv_id":"2509.25424","last_updated":"2026-05-03T20:02:35Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-09-29T19:32:11Z","title":"Polychromic Objectives for Reinforcement Learning","version":6},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-05-18T11:54:29.955833Z"},"links":{"cited_paper":"/paper/2412.16720","citing_paper":"/paper/2509.25424"},"observation_digest":"sha256:b47ccfc45bcb60597c21380872093a8e3974413865c052bb586dc09aa8e5fe33","observation_id":"aa64cf93-90a0-4ba0-851a-a2a8f0997d06","resolution":{"observed_at":"2026-05-18T11:56:19.849526Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.16720","last_updated":"2026-04-30T02:46:40Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-12-21T18:04:31Z","title":"OpenAI o1 System Card","version":2},"cited_work":{"arxiv_id":"2412.16720","doi":"10.48550/arxiv.2412.16720","metadata_source":"pith","pith_arxiv_id":"2412.16720","snapshot_observed_at":"2026-07-11T03:17:51.754565Z","title":"OpenAI o1 System Card","venue":"cs.AI","work_id":"68d3c334-0fc9-49e3-b7b0-a69afae933e2","year":2024},"citing_paper":{"arxiv_id":"2509.25454","last_updated":"2026-04-06T19:16:24Z","snapshot_observed_at":"2026-07-06T22:31:10.099674Z","submitted_at":"2025-09-29T20:00:29Z","title":"DeepSearch: Overcome the Bottleneck of Reinforcement Learning with Verifiable Rewards via Monte Carlo Tree Search","version":4},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-05-18T12:12:25.437344Z"},"links":{"cited_paper":"/paper/2412.16720","citing_paper":"/paper/2509.25454"},"observation_digest":"sha256:741b47596183707b0d44f4b5cf2e88e4f3a8db1f8b43d15759f659511177bbcb","observation_id":"1098bbcf-d623-4681-8586-c7ded60e23cb","resolution":{"observed_at":"2026-05-18T12:12:35.928771Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}}],"links":{"evidence":"/evidence","html":"/paper/2412.16720/citation-record","integrity":"/paper/2412.16720/integrity","json":"/paper/2412.16720/citation-record.json","paper":"/paper/2412.16720"},"outbound":[{"citation":{"cited_paper":null,"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":"raw_reference","pith_arxiv_id":null,"snapshot_observed_at":"2026-06-05T21:23:00.469572Z","title":"Deliberative alignment: Reasoning enables safer language models","venue":null,"work_id":"bf3c6779-1d80-4064-8815-694a243016da","year":2024},"citing_paper":{"arxiv_id":"2412.16720","last_updated":"2026-04-30T02:46:40Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-12-21T18:04:31Z","title":"OpenAI o1 System Card","version":2},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-05-23T06:39:44.542350Z"},"links":{"citing_paper":"/paper/2412.16720"},"observation_digest":"sha256:7f6e6e5fbafd0b5ecf38bfeff64e9b6fdf60720f5c840eab14b56aef976f5b3f","observation_id":"ac4f10ad-7419-4541-8ecf-0aabca69f09c","resolution":{"observed_at":"2026-05-23T06:42:40.671003Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2110.08193","last_updated":"2022-03-16T01:35:45Z","snapshot_observed_at":"2026-07-06T11:58:21.596920Z","submitted_at":"2021-10-15T16:43:46Z","title":"BBQ: A Hand-Built Bias Benchmark for Question Answering","version":2},"cited_work":{"arxiv_id":"2110.08193","doi":null,"metadata_source":"pith","pith_arxiv_id":"2110.08193","snapshot_observed_at":"2026-07-04T19:50:11.112541Z","title":"BBQ: A Hand-Built Bias Benchmark for Question Answering","venue":"cs.CL","work_id":"6f78b350-8a2a-4d00-9090-41971c52baaf","year":2021},"citing_paper":{"arxiv_id":"2412.16720","last_updated":"2026-04-30T02:46:40Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-12-21T18:04:31Z","title":"OpenAI o1 System Card","version":2},"reference_index":2,"source":"pdf_text","source_observed_at":"2026-05-23T06:39:44.542350Z"},"links":{"cited_paper":"/paper/2110.08193","citing_paper":"/paper/2412.16720"},"observation_digest":"sha256:bf33473430afc1311c0c199ba902317a3ff9545abf86a36c65a279ea7fa7de39","observation_id":"a1dd87fe-d0c5-44fb-bb61-a7b86163e221","resolution":{"observed_at":"2026-05-23T06:42:39.669631Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+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":"2026-06-05T21:23:00.469572Z","title":"On the dangers of stochastic parrots: Can language models be too big?","venue":null,"work_id":"3d2b349b-f1f4-445c-ab0c-755a01072d19","year":2021},"citing_paper":{"arxiv_id":"2412.16720","last_updated":"2026-04-30T02:46:40Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-12-21T18:04:31Z","title":"OpenAI o1 System Card","version":2},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-05-23T06:39:44.542350Z"},"links":{"citing_paper":"/paper/2412.16720"},"observation_digest":"sha256:d40868b077b65a20fe9c72ce807224b2df2214adc38831e03a35ed0a4462f48a","observation_id":"d1118f4b-2cc2-48f9-8c04-4475943ccec4","resolution":{"observed_at":"2026-05-23T06:42:40.692459Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2005.00661","last_updated":"2020-05-02T00:09:16Z","snapshot_observed_at":"2026-07-06T09:16:59.519524Z","submitted_at":"2020-05-02T00:09:16Z","title":"On Faithfulness and Factuality in Abstractive Summarization","version":1},"cited_work":{"arxiv_id":"2005.00661","doi":"10.48550/arxiv.2005.00661","metadata_source":"arxiv_reference","pith_arxiv_id":"2005.00661","snapshot_observed_at":"2026-07-10T06:15:00.866473Z","title":"On faithfulness and factuality in abstractive summarization","venue":null,"work_id":"15f147fc-11ab-469e-84a9-594dfedf756c","year":2005},"citing_paper":{"arxiv_id":"2412.16720","last_updated":"2026-04-30T02:46:40Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-12-21T18:04:31Z","title":"OpenAI o1 System Card","version":2},"reference_index":4,"source":"pdf_text","source_observed_at":"2026-05-23T06:39:44.542350Z"},"links":{"cited_paper":"/paper/2005.00661","citing_paper":"/paper/2412.16720"},"observation_digest":"sha256:76e65bf78b151e3f496ac9d9c7fd891a4053f31c6868e86b188d1e20b1e196e5","observation_id":"a4ea0f61-dce2-4275-90c8-0873266b34ec","resolution":{"observed_at":"2026-05-23T06:42:39.629137Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2403.13793","last_updated":"2024-04-05T12:26:11Z","snapshot_observed_at":"2026-08-03T18:07:25.978533Z","submitted_at":"2024-03-20T17:54:26Z","title":"Evaluating Frontier Models for Dangerous Capabilities","version":2},"cited_work":{"arxiv_id":"2403.13793","doi":"10.48550/arxiv.2403.13793","metadata_source":"pith","pith_arxiv_id":"2403.13793","snapshot_observed_at":"2026-07-10T06:15:00.866473Z","title":"Evaluating frontier models for dangerous capabilities","venue":"cs.LG","work_id":"2f7df923-9116-4ade-9fca-e78987af4e53","year":2024},"citing_paper":{"arxiv_id":"2412.16720","last_updated":"2026-04-30T02:46:40Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-12-21T18:04:31Z","title":"OpenAI o1 System Card","version":2},"reference_index":5,"source":"pdf_text","source_observed_at":"2026-05-23T06:39:44.542350Z"},"links":{"cited_paper":"/paper/2403.13793","citing_paper":"/paper/2412.16720"},"observation_digest":"sha256:12102ab82de1ce7a1b21964306b75cfffe6598ca76c4a4d5d1f19fbfa8b8bb52","observation_id":"f85bd960-a8cd-4ffc-8e96-fbaf221f5797","resolution":{"observed_at":"2026-05-23T06:42:39.642455Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+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":"2026-06-05T21:23:00.469572Z","title":"Model evaluation for extreme risks","venue":null,"work_id":"b69c300c-747b-457d-ab93-7aa1b00fd7c7","year":2023},"citing_paper":{"arxiv_id":"2412.16720","last_updated":"2026-04-30T02:46:40Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-12-21T18:04:31Z","title":"OpenAI o1 System Card","version":2},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-05-23T06:39:44.542350Z"},"links":{"citing_paper":"/paper/2412.16720"},"observation_digest":"sha256:5907a0c5c22b149762f3a0f822007d677cd966f81adcf46cfa301359b3ff913c","observation_id":"2dbc0309-d118-4341-be20-90fbd7eaf0b3","resolution":{"observed_at":"2026-05-23T06:42:40.689105Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+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":"2026-06-05T21:23:00.469572Z","title":"Red teaming network","venue":null,"work_id":"e794c579-7c75-4e58-9eb7-2c370cf05191","year":2024},"citing_paper":{"arxiv_id":"2412.16720","last_updated":"2026-04-30T02:46:40Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-12-21T18:04:31Z","title":"OpenAI o1 System Card","version":2},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-05-23T06:39:44.542350Z"},"links":{"citing_paper":"/paper/2412.16720"},"observation_digest":"sha256:e16c0ddcde004636de3fbb67d8c27eda6e9fa4f5adb229366dc07d77117745dd","observation_id":"9753111d-16e8-4b87-b688-e580858aac31","resolution":{"observed_at":"2026-05-23T06:42:40.698472Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2209.07858","last_updated":"2022-11-22T19:12:57Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2022-08-23T23:37:14Z","title":"Red Teaming Language Models to Reduce Harms: Methods, Scaling Behaviors, and Lessons Learned","version":2},"cited_work":{"arxiv_id":"2209.07858","doi":"10.1136/bcr-2013-201554","metadata_source":"pith","pith_arxiv_id":"2209.07858","snapshot_observed_at":"2026-07-11T11:50:26.030339Z","title":"Red Teaming Language Models to Reduce Harms: Methods, Scaling Behaviors, and Lessons Learned","venue":"cs.CL","work_id":"1aabd84d-3779-4ba9-ba2f-15ce264a9b1e","year":2022},"citing_paper":{"arxiv_id":"2412.16720","last_updated":"2026-04-30T02:46:40Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-12-21T18:04:31Z","title":"OpenAI o1 System Card","version":2},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-05-23T06:39:44.542350Z"},"links":{"cited_paper":"/paper/2209.07858","citing_paper":"/paper/2412.16720"},"observation_digest":"sha256:d5b55e1eab2e24aaf01c5d52200ffc289b0758baeb6bc7e3dc02f1c204f80ed1","observation_id":"843831e2-617d-4580-bc53-5d9d42741991","resolution":{"observed_at":"2026-05-23T06:42:39.637787Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+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":"2026-06-05T21:23:00.469572Z","title":"Red-teaming for generative ai: Silver bullet or security theater?","venue":null,"work_id":"dbe0eb21-c1d1-4362-ad67-d9f07b5ffa68","year":2024},"citing_paper":{"arxiv_id":"2412.16720","last_updated":"2026-04-30T02:46:40Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-12-21T18:04:31Z","title":"OpenAI o1 System Card","version":2},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-05-23T06:39:44.542350Z"},"links":{"citing_paper":"/paper/2412.16720"},"observation_digest":"sha256:dc2f2d8d582f9251fc81424cfce85189218169b49009b5220d4950f5fd4c1f53","observation_id":"60593805-d3ca-4aac-b2b2-86ede9a89a45","resolution":{"observed_at":"2026-05-23T06:42:40.712564Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+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":"2026-06-05T21:23:00.469572Z","title":"Toward trustworthy ai development: Mechanisms for supporting verifiable claims","venue":null,"work_id":"013e537c-14f4-4908-ab94-9afb10d76b8f","year":2020},"citing_paper":{"arxiv_id":"2412.16720","last_updated":"2026-04-30T02:46:40Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-12-21T18:04:31Z","title":"OpenAI o1 System Card","version":2},"reference_index":10,"source":"pdf_text","source_observed_at":"2026-05-23T06:39:44.542350Z"},"links":{"citing_paper":"/paper/2412.16720"},"observation_digest":"sha256:c46e5882ec95e253e9b045d5490d894ca7c02eef0f82e6e6214e09ead21d51e1","observation_id":"3d273a5d-53d2-40e4-8b77-c586dbd2b073","resolution":{"observed_at":"2026-05-23T06:42:40.676305Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+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":"2026-06-05T21:23:00.469572Z","title":"Gpt-4 technical report","venue":null,"work_id":"87056200-9858-4f14-8f13-4c42bb086d68","year":2024},"citing_paper":{"arxiv_id":"2412.16720","last_updated":"2026-04-30T02:46:40Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-12-21T18:04:31Z","title":"OpenAI o1 System Card","version":2},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-05-23T06:39:44.542350Z"},"links":{"citing_paper":"/paper/2412.16720"},"observation_digest":"sha256:7843ec876403273d05a6e0e621c1891ef3f3c447aa52b337d0978899c0b54dda","observation_id":"549eb6da-3704-4d75-848e-00f6d333a5ca","resolution":{"observed_at":"2026-05-23T06:42:40.679901Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+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":"2026-06-05T21:23:00.469572Z","title":"A holistic approach to undesired content detection in the real world","venue":null,"work_id":"c9ace526-a0f6-4393-9a94-81c96fb6421c","year":2023},"citing_paper":{"arxiv_id":"2412.16720","last_updated":"2026-04-30T02:46:40Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-12-21T18:04:31Z","title":"OpenAI o1 System Card","version":2},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-05-23T06:39:44.542350Z"},"links":{"citing_paper":"/paper/2412.16720"},"observation_digest":"sha256:bf66aae9c825c3f667b46c75d71fa88d500a45001587ba38c3af647f82ff9d05","observation_id":"72ad5154-eaee-4233-979a-675c03d7fb04","resolution":{"observed_at":"2026-05-23T06:42:40.664429Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2405.01470","last_updated":"2024-05-02T17:00:02Z","snapshot_observed_at":"2026-07-06T18:08:56.480769Z","submitted_at":"2024-05-02T17:00:02Z","title":"WildChat: 1M ChatGPT Interaction Logs in the Wild","version":1},"cited_work":{"arxiv_id":"2405.01470","doi":"10.48550/arxiv.2405.01470","metadata_source":"pith","pith_arxiv_id":"2405.01470","snapshot_observed_at":"2026-07-10T06:15:00.866473Z","title":"WildChat: 1M ChatGPT Interaction Logs in the Wild","venue":"cs.CL","work_id":"799d0d7b-7d66-40bb-b17f-205e5d2f3e13","year":2024},"citing_paper":{"arxiv_id":"2412.16720","last_updated":"2026-04-30T02:46:40Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-12-21T18:04:31Z","title":"OpenAI o1 System Card","version":2},"reference_index":13,"source":"pdf_text","source_observed_at":"2026-05-23T06:39:44.542350Z"},"links":{"cited_paper":"/paper/2405.01470","citing_paper":"/paper/2412.16720"},"observation_digest":"sha256:aa651b6e19ddfdc01375dc5565781f2f1a471c7ea8f6cc45a07c0eccdea6cea8","observation_id":"63d04397-daff-4f1e-bba8-997eae922800","resolution":{"observed_at":"2026-05-23T06:42:39.618391Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2308.01263","last_updated":"2024-04-01T11:50:35Z","snapshot_observed_at":"2026-08-03T00:58:55.865010Z","submitted_at":"2023-08-02T16:30:40Z","title":"XSTest: A Test Suite for Identifying Exaggerated Safety Behaviours in Large Language Models","version":3},"cited_work":{"arxiv_id":"2308.01263","doi":"10.48550/arxiv.2308.01263","metadata_source":"pith","pith_arxiv_id":"2308.01263","snapshot_observed_at":"2026-07-10T06:15:00.866473Z","title":"XSTest: A Test Suite for Identifying Exaggerated Safety Behaviours in Large Language Models","venue":"cs.CL","work_id":"bd953600-1547-4c1e-ade7-219a9f7cfe7a","year":2023},"citing_paper":{"arxiv_id":"2412.16720","last_updated":"2026-04-30T02:46:40Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-12-21T18:04:31Z","title":"OpenAI o1 System Card","version":2},"reference_index":14,"source":"pdf_text","source_observed_at":"2026-05-23T06:39:44.542350Z"},"links":{"cited_paper":"/paper/2308.01263","citing_paper":"/paper/2412.16720"},"observation_digest":"sha256:1aa060ad9d3ddaabe4648879d2bb77de36afc2ab51e3d8de3d252cfe7d054f8f","observation_id":"7ee4255b-bd71-44ba-af3e-59c44d128a52","resolution":{"observed_at":"2026-05-23T06:42:39.646916Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2308.03825","last_updated":"2024-05-15T12:06:31Z","snapshot_observed_at":"2026-07-06T16:03:34.432602Z","submitted_at":"2023-08-07T16:55:20Z","title":"\"Do Anything Now\": Characterizing and Evaluating In-The-Wild Jailbreak Prompts on Large Language Models","version":2},"cited_work":{"arxiv_id":"2308.03825","doi":null,"metadata_source":"pith","pith_arxiv_id":"2308.03825","snapshot_observed_at":"2026-07-10T17:17:25.614333Z","title":"\"Do Anything Now\": Characterizing and Evaluating In-The-Wild Jailbreak Prompts on Large Language Models","venue":"cs.CR","work_id":"73c8e776-cd59-4029-b3fe-4579d64d9014","year":2023},"citing_paper":{"arxiv_id":"2412.16720","last_updated":"2026-04-30T02:46:40Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-12-21T18:04:31Z","title":"OpenAI o1 System Card","version":2},"reference_index":15,"source":"pdf_text","source_observed_at":"2026-05-23T06:39:44.542350Z"},"links":{"cited_paper":"/paper/2308.03825","citing_paper":"/paper/2412.16720"},"observation_digest":"sha256:edc8cb7fcfee5b428651ebffedac04f94ebeba31facfbf93e4a7ef53e21c24a9","observation_id":"46e587ba-76ba-43e2-8149-78bb410d6bea","resolution":{"observed_at":"2026-05-23T06:42:39.652695Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2402.10260","last_updated":"2024-08-27T03:32:47Z","snapshot_observed_at":"2026-07-06T17:30:51.898267Z","submitted_at":"2024-02-15T18:58:09Z","title":"A StrongREJECT for Empty Jailbreaks","version":2},"cited_work":{"arxiv_id":"2402.10260","doi":"10.48550/arxiv.2402.10260","metadata_source":"pith","pith_arxiv_id":"2402.10260","snapshot_observed_at":"2026-07-10T06:15:00.866473Z","title":"A StrongREJECT for Empty Jailbreaks","venue":"cs.LG","work_id":"27281d18-31bd-4124-9fa7-4e61945ff9d1","year":2024},"citing_paper":{"arxiv_id":"2412.16720","last_updated":"2026-04-30T02:46:40Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-12-21T18:04:31Z","title":"OpenAI o1 System Card","version":2},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-05-23T06:39:44.542350Z"},"links":{"cited_paper":"/paper/2402.10260","citing_paper":"/paper/2412.16720"},"observation_digest":"sha256:ccff48ed2b3b8ccb8bb2ca346805d796c4f586abe213d8b1515110d7fea8b1dc","observation_id":"805cf1f0-4000-450f-939c-39cbf9430b3f","resolution":{"observed_at":"2026-05-23T06:42:39.658975Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-05-22T21:23:22.243424+00:00","source":"crossref_status_cache"},{"observed_at":"2026-05-22T21:23:22.243424+00:00","source":"openalex_status_cache"},{"observed_at":"2026-08-04T06:33:57.428241+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":"2026-06-05T21:23:00.469572Z","title":"Jailbreaking black box large language models in twenty queries","venue":null,"work_id":"af77621b-28e4-4dc2-a4c2-eb32ce0f5714","year":2024},"citing_paper":{"arxiv_id":"2412.16720","last_updated":"2026-04-30T02:46:40Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-12-21T18:04:31Z","title":"OpenAI o1 System Card","version":2},"reference_index":17,"source":"pdf_text","source_observed_at":"2026-05-23T06:39:44.542350Z"},"links":{"citing_paper":"/paper/2412.16720"},"observation_digest":"sha256:59dee49c2d577f4725e902317bf8d8c94cdc531a96acf20e3d78d6ce6e40ce85","observation_id":"4f265c4f-ec9f-4e6c-b86e-6a700ba53dfa","resolution":{"observed_at":"2026-05-23T06:42:40.708877Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+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":"2026-06-05T21:23:00.469572Z","title":"Jailbreakbench: An open robustness benchmark for jailbreaking large language models","venue":null,"work_id":"78b2b68b-d563-4893-8f15-eede56b299b1","year":2024},"citing_paper":{"arxiv_id":"2412.16720","last_updated":"2026-04-30T02:46:40Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-12-21T18:04:31Z","title":"OpenAI o1 System Card","version":2},"reference_index":18,"source":"pdf_text","source_observed_at":"2026-05-23T06:39:44.542350Z"},"links":{"citing_paper":"/paper/2412.16720"},"observation_digest":"sha256:fb1052463f83664f49d3e3b236b69aa5cb85ff9a1e1111af05f1e8cafa0c428b","observation_id":"b152606f-6f4b-48e8-8a94-82342ccb33e0","resolution":{"observed_at":"2026-05-23T06:42:40.705421Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2312.03689","last_updated":"2023-12-06T18:53:01Z","snapshot_observed_at":"2026-07-06T16:57:51.263433Z","submitted_at":"2023-12-06T18:53:01Z","title":"Evaluating and Mitigating Discrimination in Language Model Decisions","version":1},"cited_work":{"arxiv_id":"2312.03689","doi":"10.48550/arxiv.2312.03689","metadata_source":"arxiv_reference","pith_arxiv_id":"2312.03689","snapshot_observed_at":"2026-07-10T06:15:00.866473Z","title":"& Ganguli, D","venue":null,"work_id":"f998a9d9-5425-4854-bde3-98409636f357","year":2022},"citing_paper":{"arxiv_id":"2412.16720","last_updated":"2026-04-30T02:46:40Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-12-21T18:04:31Z","title":"OpenAI o1 System Card","version":2},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-05-23T06:39:44.542350Z"},"links":{"cited_paper":"/paper/2312.03689","citing_paper":"/paper/2412.16720"},"observation_digest":"sha256:433ac9b5e91ee7d8d8cfb546853676e5fb8ca576526ce42e80f07329df52a444","observation_id":"65d93c4e-d32c-4c21-bd00-211851f46131","resolution":{"observed_at":"2026-05-23T06:42:39.674874Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+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":"2026-06-05T21:23:00.469572Z","title":"The instruction hierarchy: Training llms to prioritize privileged instructions","venue":null,"work_id":"7b0c0318-ba4c-451b-8cfc-d99cf27a557e","year":2024},"citing_paper":{"arxiv_id":"2412.16720","last_updated":"2026-04-30T02:46:40Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-12-21T18:04:31Z","title":"OpenAI o1 System Card","version":2},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-05-23T06:39:44.542350Z"},"links":{"citing_paper":"/paper/2412.16720"},"observation_digest":"sha256:0e5ab5a5ccb79412fcfc5a5ecce1633a56d3238ae15df8caa759a9bb6471267e","observation_id":"a62f28f9-92cc-4d56-b053-29a79f8901a8","resolution":{"observed_at":"2026-05-23T06:42:40.701777Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2307.13702","last_updated":"2023-07-17T01:08:39Z","snapshot_observed_at":"2026-07-31T04:21:27.501709Z","submitted_at":"2023-07-17T01:08:39Z","title":"Measuring Faithfulness in Chain-of-Thought Reasoning","version":1},"cited_work":{"arxiv_id":"2307.13702","doi":"10.48550/arxiv.2307.13702","metadata_source":"pith","pith_arxiv_id":"2307.13702","snapshot_observed_at":"2026-07-11T00:37:43.053081Z","title":"Measuring Faithfulness in Chain-of-Thought Reasoning","venue":"cs.AI","work_id":"86ca07b8-4628-4f51-8938-a82683386ae4","year":2023},"citing_paper":{"arxiv_id":"2412.16720","last_updated":"2026-04-30T02:46:40Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-12-21T18:04:31Z","title":"OpenAI o1 System Card","version":2},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-05-23T06:39:44.542350Z"},"links":{"cited_paper":"/paper/2307.13702","citing_paper":"/paper/2412.16720"},"observation_digest":"sha256:597af35fee8339e27ae0465c0806dd6ea3099e5d03e2c690f0fb892abdc2d20e","observation_id":"fd8ae6bc-7013-42c1-b2d9-fddb5c5d0ab7","resolution":{"observed_at":"2026-05-23T06:42:39.679765Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+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":"2026-06-05T21:23:00.469572Z","title":"Language models don’t always say what they think: unfaithful explanations in chain-of-thought prompting","venue":null,"work_id":"72af09a8-82bd-4b8f-922a-dee49e240931","year":2024},"citing_paper":{"arxiv_id":"2412.16720","last_updated":"2026-04-30T02:46:40Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-12-21T18:04:31Z","title":"OpenAI o1 System Card","version":2},"reference_index":22,"source":"pdf_text","source_observed_at":"2026-05-23T06:39:44.542350Z"},"links":{"citing_paper":"/paper/2412.16720"},"observation_digest":"sha256:61fa0560034d5d52be750847390ba72a280c8b18213bb1b1ffb9696c2b0887c4","observation_id":"aeba6c04-4f71-4e5f-b5bf-44359d51bf52","resolution":{"observed_at":"2026-05-23T06:42:40.695441Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2406.10625","last_updated":"2024-07-01T13:36:29Z","snapshot_observed_at":"2026-07-06T18:31:32.118399Z","submitted_at":"2024-06-15T13:16:44Z","title":"On the Hardness of Faithful Chain-of-Thought Reasoning in Large Language Models","version":2},"cited_work":{"arxiv_id":"2406.10625","doi":"10.48550/arxiv.2406.10625","metadata_source":"arxiv_reference","pith_arxiv_id":"2406.10625","snapshot_observed_at":"2026-07-10T06:15:00.866473Z","title":"On the hardness of faithful chain-of-thought reasoning in large language models","venue":null,"work_id":"7b24c8d0-8360-4c5d-907e-d78a2c837984","year":2018},"citing_paper":{"arxiv_id":"2412.16720","last_updated":"2026-04-30T02:46:40Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-12-21T18:04:31Z","title":"OpenAI o1 System Card","version":2},"reference_index":23,"source":"pdf_text","source_observed_at":"2026-05-23T06:39:44.542350Z"},"links":{"cited_paper":"/paper/2406.10625","citing_paper":"/paper/2412.16720"},"observation_digest":"sha256:327b88c8b14f4165049fa684a349c223c88e4b02b43e5c7c34fba1c275103ad9","observation_id":"3075a40c-559d-4350-aab4-89c5e76f6332","resolution":{"observed_at":"2026-05-23T06:42:39.624072Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2402.04614","last_updated":"2024-03-14T03:48:08Z","snapshot_observed_at":"2026-08-03T06:52:15.782895Z","submitted_at":"2024-02-07T06:32:50Z","title":"Faithfulness vs. Plausibility: On the (Un)Reliability of Explanations from Large Language Models","version":3},"cited_work":{"arxiv_id":"2402.04614","doi":"10.48550/arxiv.2402.04614","metadata_source":"arxiv_reference","pith_arxiv_id":"2402.04614","snapshot_observed_at":"2026-07-10T06:15:00.866473Z","title":"plausibility: On the (un)reliability of explanations from large language models","venue":null,"work_id":"55cbc155-adcb-4c5a-b5c9-0cf199284251","year":2024},"citing_paper":{"arxiv_id":"2412.16720","last_updated":"2026-04-30T02:46:40Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-12-21T18:04:31Z","title":"OpenAI o1 System Card","version":2},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-05-23T06:39:44.542350Z"},"links":{"cited_paper":"/paper/2402.04614","citing_paper":"/paper/2412.16720"},"observation_digest":"sha256:7ce7cd6967d39d425b2e012158174b08c5bbd339d233555a30aaea732fceb6f7","observation_id":"b9f1e6d8-dbaf-4d73-9b7b-12fc3a257cbc","resolution":{"observed_at":"2026-05-23T06:42:39.633867Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2405.01576","last_updated":"2024-04-25T17:29:53Z","snapshot_observed_at":"2026-07-06T18:09:00.688840Z","submitted_at":"2024-04-25T17:29:53Z","title":"Uncovering Deceptive Tendencies in Language Models: A Simulated Company AI Assistant","version":1},"cited_work":{"arxiv_id":"2405.01576","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2405.01576","snapshot_observed_at":"2026-07-02T17:07:13.036229Z","title":"Uncovering deceptive tendencies in language models: A simulated company ai assistant","venue":null,"work_id":"eee3283b-1292-41dc-b3da-05ff86b5ceb5","year":2024},"citing_paper":{"arxiv_id":"2412.16720","last_updated":"2026-04-30T02:46:40Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-12-21T18:04:31Z","title":"OpenAI o1 System Card","version":2},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-05-23T06:39:44.542350Z"},"links":{"cited_paper":"/paper/2405.01576","citing_paper":"/paper/2412.16720"},"observation_digest":"sha256:8ab0b28a47495c5317f025a705b4dbc477c04565ee1d70b0f432365cad130554","observation_id":"37160e69-f16d-4b99-a44e-acd3993e457f","resolution":{"observed_at":"2026-05-23T06:42:39.664420Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+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":"2026-06-05T21:23:00.469572Z","title":"Deception abilities emerged in large language models","venue":null,"work_id":"41e4c6b9-b5e1-492f-9363-bcf320e6e9de","year":2024},"citing_paper":{"arxiv_id":"2412.16720","last_updated":"2026-04-30T02:46:40Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-12-21T18:04:31Z","title":"OpenAI o1 System Card","version":2},"reference_index":26,"source":"pdf_text","source_observed_at":"2026-05-23T06:39:44.542350Z"},"links":{"citing_paper":"/paper/2412.16720"},"observation_digest":"sha256:afecb678818b8e60c3376df363269f085d3b2ca98ec90488536658b7b3bcdc29","observation_id":"10d5bc0e-f824-4591-bf8b-31d5e19eec30","resolution":{"observed_at":"2026-05-23T06:42:40.667950Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+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":"2026-06-05T21:23:00.469572Z","title":"Openai’s approach to external red teaming","venue":null,"work_id":"8c24145a-40e1-4228-8bf2-d7a47a1b4138","year":2024},"citing_paper":{"arxiv_id":"2412.16720","last_updated":"2026-04-30T02:46:40Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-12-21T18:04:31Z","title":"OpenAI o1 System Card","version":2},"reference_index":27,"source":"pdf_text","source_observed_at":"2026-05-23T06:39:44.542350Z"},"links":{"citing_paper":"/paper/2412.16720"},"observation_digest":"sha256:d6c9875562ca782bf24d7a345b6e3cf1576ae5210d1c0a105ab61e107770ea16","observation_id":"27ddb81e-e917-45f4-9d7c-223db4e504fa","resolution":{"observed_at":"2026-05-23T06:42:40.686416Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+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":"2026-06-05T21:23:00.469572Z","title":"Openai preparedness framework (beta)","venue":null,"work_id":"8877adc7-9264-4011-a891-5294450e6355","year":2023},"citing_paper":{"arxiv_id":"2412.16720","last_updated":"2026-04-30T02:46:40Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-12-21T18:04:31Z","title":"OpenAI o1 System Card","version":2},"reference_index":28,"source":"pdf_text","source_observed_at":"2026-05-23T06:39:44.542350Z"},"links":{"citing_paper":"/paper/2412.16720"},"observation_digest":"sha256:5f17511725e36f57ed4c01afdae91ce3f1e584d5fb12f396f8be963de835ccc5","observation_id":"ecd37509-2b2e-4b85-b41a-6fa908c25d86","resolution":{"observed_at":"2026-05-23T06:42:40.683103Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+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":"2026-06-05T21:23:00.469572Z","title":"Csaw cybersecurity games & conference","venue":null,"work_id":"371df545-f3ec-4654-872d-eca1016a00a8","year":2013},"citing_paper":{"arxiv_id":"2412.16720","last_updated":"2026-04-30T02:46:40Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-12-21T18:04:31Z","title":"OpenAI o1 System Card","version":2},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-05-23T06:39:44.542350Z"},"links":{"citing_paper":"/paper/2412.16720"},"observation_digest":"sha256:58323848211f39024371f8283ca594cdca1f78542988169638e4651b5f2925f2","observation_id":"1b61a651-cced-4141-af71-2227e65950c1","resolution":{"observed_at":"2026-05-23T06:42:40.661530Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+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":"2026-06-05T21:23:00.469572Z","title":"Building an early warning system for llm-aided biological threat creation","venue":null,"work_id":"c8622ce2-c4de-4fa2-9d1e-7c882bd44441","year":2023},"citing_paper":{"arxiv_id":"2412.16720","last_updated":"2026-04-30T02:46:40Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-12-21T18:04:31Z","title":"OpenAI o1 System Card","version":2},"reference_index":30,"source":"pdf_text","source_observed_at":"2026-05-23T06:39:44.542350Z"},"links":{"citing_paper":"/paper/2412.16720"},"observation_digest":"sha256:ec8dc1f3146ad1c53482b09d1230fba505fde2c5165d65f1922bdec5acae5222","observation_id":"eeb68398-6244-4ba2-ac9c-895188773084","resolution":{"observed_at":"2026-05-23T06:42:40.648480Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+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":"2026-06-05T21:23:00.469572Z","title":"Lab-bench: Measuring capabilities of language models for biology research","venue":null,"work_id":"ba6aabbd-5e5e-491f-a95b-9b4dc54edc25","year":2024},"citing_paper":{"arxiv_id":"2412.16720","last_updated":"2026-04-30T02:46:40Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-12-21T18:04:31Z","title":"OpenAI o1 System Card","version":2},"reference_index":31,"source":"pdf_text","source_observed_at":"2026-05-23T06:39:44.542350Z"},"links":{"citing_paper":"/paper/2412.16720"},"observation_digest":"sha256:07c0ee94bb9c210b63bd7ded2eb6951c43ccbca896b05d8e314d93127abb7ba4","observation_id":"adb0b942-f38f-499e-8c0b-1619c49c323a","resolution":{"observed_at":"2026-05-23T06:42:40.651738Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+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":"2026-06-05T21:23:00.469572Z","title":"Biolp-bench: Measuring understanding of ai models of biological lab protocols","venue":null,"work_id":"40c3e41f-161c-4b65-9891-6ccca4e60ea6","year":2024},"citing_paper":{"arxiv_id":"2412.16720","last_updated":"2026-04-30T02:46:40Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-12-21T18:04:31Z","title":"OpenAI o1 System Card","version":2},"reference_index":32,"source":"pdf_text","source_observed_at":"2026-05-23T06:39:44.542350Z"},"links":{"citing_paper":"/paper/2412.16720"},"observation_digest":"sha256:df523599a3c39666d2f1cc2558c2712a9126036fc625e7c33ed1176e49525168","observation_id":"1dabff19-f486-439c-b480-3e5935498608","resolution":{"observed_at":"2026-05-23T06:42:40.655179Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+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":"2026-06-05T21:23:00.469572Z","title":"Winning arguments: Interaction dynamics and persuasion strategies in good-faith online discussions","venue":null,"work_id":"9b91ae54-b800-45c7-a157-a2f7d4f793dc","year":2016},"citing_paper":{"arxiv_id":"2412.16720","last_updated":"2026-04-30T02:46:40Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-12-21T18:04:31Z","title":"OpenAI o1 System Card","version":2},"reference_index":33,"source":"pdf_text","source_observed_at":"2026-05-23T06:39:44.542350Z"},"links":{"citing_paper":"/paper/2412.16720"},"observation_digest":"sha256:03705eaa108575fcdcdd9a76e787a76577550b16ae004e60f3094bb10b187fb2","observation_id":"8f6dba24-f679-49d1-8673-dd97e4ecc1be","resolution":{"observed_at":"2026-05-23T06:42:40.640956Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+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":"2026-06-05T21:23:00.469572Z","title":"Makemepay","venue":null,"work_id":"994388f0-9d67-400f-a832-d01c4087a0db","year":2023},"citing_paper":{"arxiv_id":"2412.16720","last_updated":"2026-04-30T02:46:40Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-12-21T18:04:31Z","title":"OpenAI o1 System Card","version":2},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-05-23T06:39:44.542350Z"},"links":{"citing_paper":"/paper/2412.16720"},"observation_digest":"sha256:26c024ca6aa92ee525e44c712bb8e5003fe531d757ec7faf623752264b8bbc16","observation_id":"c1a4c570-2ba2-4d95-987b-583d146026b6","resolution":{"observed_at":"2026-05-23T06:42:40.643853Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+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":"2026-06-05T21:23:00.469572Z","title":"Makemesay","venue":null,"work_id":"fc33ba94-ab99-49b6-8e01-c1e2bf075a7a","year":2023},"citing_paper":{"arxiv_id":"2412.16720","last_updated":"2026-04-30T02:46:40Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-12-21T18:04:31Z","title":"OpenAI o1 System Card","version":2},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-05-23T06:39:44.542350Z"},"links":{"citing_paper":"/paper/2412.16720"},"observation_digest":"sha256:44febf3acc734ca7c3f77decc656a93bda705a299b1a34a9a3ba518da612745e","observation_id":"f9347a6d-90c4-494d-be89-c709b0b202c9","resolution":{"observed_at":"2026-05-23T06:42:40.633849Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+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":"2026-06-05T21:23:00.469572Z","title":"Introducing swe-bench verified","venue":null,"work_id":"8028d60d-8db0-4d20-9521-56a52fa39575","year":2024},"citing_paper":{"arxiv_id":"2412.16720","last_updated":"2026-04-30T02:46:40Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-12-21T18:04:31Z","title":"OpenAI o1 System Card","version":2},"reference_index":36,"source":"pdf_text","source_observed_at":"2026-05-23T06:39:44.542350Z"},"links":{"citing_paper":"/paper/2412.16720"},"observation_digest":"sha256:6564c35dab569787ddccd1749fc2f8022e99b59f5e3a36ea467657be97549a7b","observation_id":"09766045-4eb1-46d1-b728-7de2d8f87619","resolution":{"observed_at":"2026-05-23T06:42:40.630630Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+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":"2026-06-05T21:23:00.469572Z","title":"Swe-bench: Can language models resolve real-world github issues?","venue":null,"work_id":"06ce93ae-a87b-46f8-bbb0-ccdf72c2d26c","year":2024},"citing_paper":{"arxiv_id":"2412.16720","last_updated":"2026-04-30T02:46:40Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-12-21T18:04:31Z","title":"OpenAI o1 System Card","version":2},"reference_index":37,"source":"pdf_text","source_observed_at":"2026-05-23T06:39:44.542350Z"},"links":{"citing_paper":"/paper/2412.16720"},"observation_digest":"sha256:79aa99563771c437bde0aeb6afdaae8e47b97bf2bea97e2f497c88e7a4eaef61","observation_id":"a6bce2a2-6157-424f-af2a-022014848d85","resolution":{"observed_at":"2026-05-23T06:42:40.637670Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+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":"2026-06-05T21:23:00.469572Z","title":"Mle-bench: Evaluating machine learning agents on machine learning engineering","venue":null,"work_id":"7fb05016-3a63-4d45-9d1b-ea1f6f9dbd15","year":2024},"citing_paper":{"arxiv_id":"2412.16720","last_updated":"2026-04-30T02:46:40Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-12-21T18:04:31Z","title":"OpenAI o1 System Card","version":2},"reference_index":38,"source":"pdf_text","source_observed_at":"2026-05-23T06:39:44.542350Z"},"links":{"citing_paper":"/paper/2412.16720"},"observation_digest":"sha256:ec1bb46f368a9c7119fab1e1b30c80ef2e998978bbef6abc1a0b2e5793d9d26a","observation_id":"ed6aa36d-afac-4360-b856-0a32ddf83118","resolution":{"observed_at":"2026-05-23T06:47:40.996032Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+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":"2026-06-05T21:23:00.469572Z","title":"Measuring massive multitask language understanding","venue":null,"work_id":"07cb2747-6cce-4a84-b8bd-af68ac59ca8c","year":2021},"citing_paper":{"arxiv_id":"2412.16720","last_updated":"2026-04-30T02:46:40Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-12-21T18:04:31Z","title":"OpenAI o1 System Card","version":2},"reference_index":39,"source":"pdf_text","source_observed_at":"2026-05-23T06:39:44.542350Z"},"links":{"citing_paper":"/paper/2412.16720"},"observation_digest":"sha256:eccbf0ff734209c64c68779b1f6a37d0ace8006151747f5966ead2a409e8b504","observation_id":"0592c856-7e30-4633-a073-0e3ad77181f9","resolution":{"observed_at":"2026-05-23T06:42:40.658346Z","resolver_source":"raw_fallback","status":"verified_fuzzy"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"state":"measured"}}],"paper":{"arxiv_id":"2412.16720","last_updated":"2026-04-30T02:46:40Z","latest_version":2,"primary_category":"cs.AI","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2024-12-21T18:04:31Z","title":"OpenAI o1 System Card"},"reference_resolution":{"displayed":39,"state_counts":{"malformed_identifier":0,"metadata_mismatch":1,"parse_uncertain":0,"unresolved":0,"verified_exact":12,"verified_fuzzy":26},"total_outbound_references":39},"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":"2026-08-04T06:34:03.388597+00:00","source":"crossref"},{"observed_at":"2026-08-04T06:33:57.428241+00:00","source":"retraction_watch"}],"thesis":"As of 4 August 2026, this Paper Citation Record lists 39 of 39 outbound references and 100 inbound Pith citation observations for arXiv:2412.16720."}