{"as_of":"2026-08-05T10:07:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:652c067c2a543be890eab4c8931ffcd95ee9481216511e822e5ec005f38a74d9","coverage":[{"denominator":0,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":16,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":16,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-05T06:32:48.257954+00:00","state":"measured"},{"denominator":16,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":16,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-04T20:21:21.815399Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"arxiv_reference","source_observed_at":"2026-06-28T22:32:44.141882Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2308.00436","last_updated":"2023-10-05T12:59:59Z","snapshot_observed_at":"2026-07-06T16:01:11.052152Z","submitted_at":"2023-08-01T10:31:36Z","title":"SelfCheck: Using LLMs to Zero-Shot Check Their Own Step-by-Step Reasoning","version":3},"cited_work":{"arxiv_id":"2308.00436","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2308.00436","snapshot_observed_at":"2026-06-28T22:32:44.141882Z","title":"arXiv preprint arXiv:2308.00436 , year=","venue":null,"work_id":"1bd8771e-344a-4981-be63-3a4e84fd2df5","year":2023},"citing_paper":{"arxiv_id":"2309.07864","last_updated":"2023-09-19T08:29:18Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-09-14T17:12:03Z","title":"The Rise and Potential of Large Language Model Based Agents: A Survey","version":3},"reference_index":193,"source":"pdf_text","source_observed_at":"2026-05-11T10:47:44.152066Z"},"links":{"cited_paper":"/paper/2308.00436","citing_paper":"/paper/2309.07864"},"observation_digest":"sha256:e646559f343e5e55844da80c6fbf7d55460f58937fe661d1cebfff81b4e06116","observation_id":"0e837d28-bad0-4b0c-a1f2-b45ca36ebb8c","resolution":{"observed_at":"2026-05-11T10:47:46.222821Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2308.00436","last_updated":"2023-10-05T12:59:59Z","snapshot_observed_at":"2026-07-06T16:01:11.052152Z","submitted_at":"2023-08-01T10:31:36Z","title":"SelfCheck: Using LLMs to Zero-Shot Check Their Own Step-by-Step Reasoning","version":3},"cited_work":{"arxiv_id":"2308.00436","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2308.00436","snapshot_observed_at":"2026-06-28T22:32:44.141882Z","title":"arXiv preprint arXiv:2308.00436 , year=","venue":null,"work_id":"1bd8771e-344a-4981-be63-3a4e84fd2df5","year":2023},"citing_paper":{"arxiv_id":"2309.11495","last_updated":"2023-09-25T15:25:49Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-09-20T17:50:55Z","title":"Chain-of-Verification Reduces Hallucination in Large Language Models","version":2},"reference_index":157,"source":"arxiv_source","source_observed_at":"2026-05-18T01:06:49.811982Z"},"links":{"cited_paper":"/paper/2308.00436","citing_paper":"/paper/2309.11495"},"observation_digest":"sha256:3c523ba92c322fbe470eea202868f73dcf31b0943474241c1106c7d0111a9846","observation_id":"38dcbf99-1582-4781-b99f-9986dc30edf1","resolution":{"observed_at":"2026-05-18T01:06:50.409824Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2308.00436","last_updated":"2023-10-05T12:59:59Z","snapshot_observed_at":"2026-07-06T16:01:11.052152Z","submitted_at":"2023-08-01T10:31:36Z","title":"SelfCheck: Using LLMs to Zero-Shot Check Their Own Step-by-Step Reasoning","version":3},"cited_work":{"arxiv_id":"2308.00436","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2308.00436","snapshot_observed_at":"2026-06-28T22:32:44.141882Z","title":"arXiv preprint arXiv:2308.00436 , year=","venue":null,"work_id":"1bd8771e-344a-4981-be63-3a4e84fd2df5","year":2023},"citing_paper":{"arxiv_id":"2311.05232","last_updated":"2024-11-19T12:42:45Z","snapshot_observed_at":"2026-07-06T16:45:07.733095Z","submitted_at":"2023-11-09T09:25:37Z","title":"A Survey on Hallucination in Large Language Models: Principles, Taxonomy, Challenges, and Open Questions","version":2},"reference_index":222,"source":"pdf_text","source_observed_at":"2026-05-13T02:46:26.957539Z"},"links":{"cited_paper":"/paper/2308.00436","citing_paper":"/paper/2311.05232"},"observation_digest":"sha256:c818c6ec247783051b588f79157f2916bba5d292e265c4dda3a00f782418c322","observation_id":"46e09913-0d9e-4aa5-b7d5-7881ad19b495","resolution":{"observed_at":"2026-05-13T02:46:27.809338Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2308.00436","last_updated":"2023-10-05T12:59:59Z","snapshot_observed_at":"2026-07-06T16:01:11.052152Z","submitted_at":"2023-08-01T10:31:36Z","title":"SelfCheck: Using LLMs to Zero-Shot Check Their Own Step-by-Step Reasoning","version":3},"cited_work":{"arxiv_id":"2308.00436","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2308.00436","snapshot_observed_at":"2026-06-28T22:32:44.141882Z","title":"arXiv preprint arXiv:2308.00436 , year=","venue":null,"work_id":"1bd8771e-344a-4981-be63-3a4e84fd2df5","year":2023},"citing_paper":{"arxiv_id":"2502.17419","last_updated":"2025-06-25T02:24:46Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2025-02-24T18:50:52Z","title":"From System 1 to System 2: A Survey of Reasoning Large Language Models","version":6},"reference_index":225,"source":"pdf_text","source_observed_at":"2026-05-13T01:36:23.845366Z"},"links":{"cited_paper":"/paper/2308.00436","citing_paper":"/paper/2502.17419"},"observation_digest":"sha256:8a4c8376215b2fc289fb8da9d4ae1fc2cac448818a66614e77298d4cb344704f","observation_id":"5e402d76-4edb-4091-8121-0de4d404c0bc","resolution":{"observed_at":"2026-05-13T01:36:24.353297Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2308.00436","last_updated":"2023-10-05T12:59:59Z","snapshot_observed_at":"2026-07-06T16:01:11.052152Z","submitted_at":"2023-08-01T10:31:36Z","title":"SelfCheck: Using LLMs to Zero-Shot Check Their Own Step-by-Step Reasoning","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2308.00436","snapshot_observed_at":"2026-08-04T20:21:21.815399Z","title":"arXiv preprint arXiv:2308.00436","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2509.08682","last_updated":"2025-09-10T15:22:00Z","snapshot_observed_at":"2026-08-04T20:21:21.285877Z","submitted_at":"2025-09-10T15:22:00Z","title":"Automatic Failure Attribution and Critical Step Prediction Method for Multi-Agent Systems Based on Causal Inference","version":1},"reference_index":11,"source":"pdf_text","source_observed_at":"2026-08-04T20:21:21.815399Z"},"links":{"cited_paper":"/paper/2308.00436","citing_paper":"/paper/2509.08682"},"observation_digest":"sha256:b306c0e51f13a9a884218b52420ec57f97411d9c7f6463daa07cf1be3c067653","observation_id":"f232e0bd-caa4-42ea-941f-10928430d000","resolution":{"observed_at":"2026-08-04T20:21:21.815399Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2308.00436","last_updated":"2023-10-05T12:59:59Z","snapshot_observed_at":"2026-07-06T16:01:11.052152Z","submitted_at":"2023-08-01T10:31:36Z","title":"SelfCheck: Using LLMs to Zero-Shot Check Their Own Step-by-Step Reasoning","version":3},"cited_work":{"arxiv_id":"2308.00436","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2308.00436","snapshot_observed_at":"2026-06-28T22:32:44.141882Z","title":"arXiv preprint arXiv:2308.00436 , year=","venue":null,"work_id":"1bd8771e-344a-4981-be63-3a4e84fd2df5","year":2023},"citing_paper":{"arxiv_id":"2605.01474","last_updated":"2026-05-02T14:44:49Z","snapshot_observed_at":"2026-07-06T23:14:43.034336Z","submitted_at":"2026-05-02T14:44:49Z","title":"ReMedi: Reasoner for Medical Clinical Prediction","version":1},"reference_index":65,"source":"arxiv_source","source_observed_at":"2026-05-09T14:20:29.672994Z"},"links":{"cited_paper":"/paper/2308.00436","citing_paper":"/paper/2605.01474"},"observation_digest":"sha256:b1f24a3ad2f8a58590ac7e0ec54437243bedef6e30d4d913c85bcaf8b4f815e8","observation_id":"54fef558-5377-49d7-b80b-18e1e2a046a8","resolution":{"observed_at":"2026-05-11T17:01:06.018535Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2308.00436","last_updated":"2023-10-05T12:59:59Z","snapshot_observed_at":"2026-07-06T16:01:11.052152Z","submitted_at":"2023-08-01T10:31:36Z","title":"SelfCheck: Using LLMs to Zero-Shot Check Their Own Step-by-Step Reasoning","version":3},"cited_work":{"arxiv_id":"2308.00436","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2308.00436","snapshot_observed_at":"2026-06-28T22:32:44.141882Z","title":"arXiv preprint arXiv:2308.00436 , year=","venue":null,"work_id":"1bd8771e-344a-4981-be63-3a4e84fd2df5","year":2023},"citing_paper":{"arxiv_id":"2605.03950","last_updated":"2026-05-05T16:36:58Z","snapshot_observed_at":"2026-07-06T23:16:49.553583Z","submitted_at":"2026-05-05T16:36:58Z","title":"UnAC: Adaptive Visual Prompting with Abstraction and Stepwise Checking for Complex Multimodal Reasoning","version":1},"reference_index":20,"source":"arxiv_source","source_observed_at":"2026-05-07T17:35:28.050906Z"},"links":{"cited_paper":"/paper/2308.00436","citing_paper":"/paper/2605.03950"},"observation_digest":"sha256:8d5f8072779dc98e14a46e40607261e2b3007f7195a3e61d067290f338342663","observation_id":"85a09185-04ef-46eb-8b4c-252abddade3a","resolution":{"observed_at":"2026-05-11T23:16:37.377658Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2308.00436","last_updated":"2023-10-05T12:59:59Z","snapshot_observed_at":"2026-07-06T16:01:11.052152Z","submitted_at":"2023-08-01T10:31:36Z","title":"SelfCheck: Using LLMs to Zero-Shot Check Their Own Step-by-Step Reasoning","version":3},"cited_work":{"arxiv_id":"2308.00436","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2308.00436","snapshot_observed_at":"2026-06-28T22:32:44.141882Z","title":"arXiv preprint arXiv:2308.00436 , year=","venue":null,"work_id":"1bd8771e-344a-4981-be63-3a4e84fd2df5","year":2023},"citing_paper":{"arxiv_id":"2605.08715","last_updated":"2026-05-13T23:06:48Z","snapshot_observed_at":"2026-07-06T23:20:52.521341Z","submitted_at":"2026-05-09T05:55:19Z","title":"AgentForesight: Online Auditing for Early Failure Prediction in Multi-Agent Systems","version":1},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-05-12T01:19:49.062330Z"},"links":{"cited_paper":"/paper/2308.00436","citing_paper":"/paper/2605.08715"},"observation_digest":"sha256:7009accf5b9e0700defc1b07136c08c54f66872dd510b4eb7030ae16648e04c7","observation_id":"2fd8b03d-6929-49a7-9060-ad9d60e770b6","resolution":{"observed_at":"2026-05-12T08:06:27.529436Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2308.00436","last_updated":"2023-10-05T12:59:59Z","snapshot_observed_at":"2026-07-06T16:01:11.052152Z","submitted_at":"2023-08-01T10:31:36Z","title":"SelfCheck: Using LLMs to Zero-Shot Check Their Own Step-by-Step Reasoning","version":3},"cited_work":{"arxiv_id":"2308.00436","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2308.00436","snapshot_observed_at":"2026-06-28T22:32:44.141882Z","title":"arXiv preprint arXiv:2308.00436 , year=","venue":null,"work_id":"1bd8771e-344a-4981-be63-3a4e84fd2df5","year":2023},"citing_paper":{"arxiv_id":"2605.08715","last_updated":"2026-05-13T23:06:48Z","snapshot_observed_at":"2026-07-06T23:20:52.521341Z","submitted_at":"2026-05-09T05:55:19Z","title":"AgentForesight: Online Auditing for Early Failure Prediction in Multi-Agent Systems","version":2},"reference_index":35,"source":"pdf_text","source_observed_at":"2026-05-15T05:24:54.265411Z"},"links":{"cited_paper":"/paper/2308.00436","citing_paper":"/paper/2605.08715"},"observation_digest":"sha256:798634edac54f89854ddce3e43490627c6bbdfa236f646313d8f8552fe82f7d0","observation_id":"2369fa24-1d32-4f0a-a595-b17acd3afbe8","resolution":{"observed_at":"2026-05-15T05:25:03.851275Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2308.00436","last_updated":"2023-10-05T12:59:59Z","snapshot_observed_at":"2026-07-06T16:01:11.052152Z","submitted_at":"2023-08-01T10:31:36Z","title":"SelfCheck: Using LLMs to Zero-Shot Check Their Own Step-by-Step Reasoning","version":3},"cited_work":{"arxiv_id":"2308.00436","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2308.00436","snapshot_observed_at":"2026-06-28T22:32:44.141882Z","title":"arXiv preprint arXiv:2308.00436 , year=","venue":null,"work_id":"1bd8771e-344a-4981-be63-3a4e84fd2df5","year":2023},"citing_paper":{"arxiv_id":"2605.12384","last_updated":"2026-05-12T16:47:40Z","snapshot_observed_at":"2026-07-06T23:24:03.984179Z","submitted_at":"2026-05-12T16:47:40Z","title":"Scalable Token-Level Hallucination Detection in Large Language Models","version":1},"reference_index":49,"source":"pdf_text","source_observed_at":"2026-05-13T05:49:23.534294Z"},"links":{"cited_paper":"/paper/2308.00436","citing_paper":"/paper/2605.12384"},"observation_digest":"sha256:f10f5aace98f1fdc82382f65dfd5468519506d4bab5c67b3204f69d8325b5bfc","observation_id":"4b0b5e31-f5cd-450c-b036-1d7e88de0909","resolution":{"observed_at":"2026-05-13T05:52:22.379615Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2308.00436","last_updated":"2023-10-05T12:59:59Z","snapshot_observed_at":"2026-07-06T16:01:11.052152Z","submitted_at":"2023-08-01T10:31:36Z","title":"SelfCheck: Using LLMs to Zero-Shot Check Their Own Step-by-Step Reasoning","version":3},"cited_work":{"arxiv_id":"2308.00436","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2308.00436","snapshot_observed_at":"2026-06-28T22:32:44.141882Z","title":"arXiv preprint arXiv:2308.00436 , year=","venue":null,"work_id":"1bd8771e-344a-4981-be63-3a4e84fd2df5","year":2023},"citing_paper":{"arxiv_id":"2605.30961","last_updated":"2026-05-29T07:56:31Z","snapshot_observed_at":"2026-07-06T23:40:12.939143Z","submitted_at":"2026-05-29T07:56:31Z","title":"EvoGens: A Population-Based Heuristic Search Framework for Scientific Idea Generation","version":1},"reference_index":42,"source":"pdf_text","source_observed_at":"2026-06-28T22:29:44.078911Z"},"links":{"cited_paper":"/paper/2308.00436","citing_paper":"/paper/2605.30961"},"observation_digest":"sha256:4b2b94b0d8ea6c0269053d5ebbc0a53cd297bfaaf2a83c2988077f4ac7dcdf84","observation_id":"cc76b331-db08-4ae1-9581-d981ca6f5540","resolution":{"observed_at":"2026-06-28T22:32:44.143341Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2308.00436","last_updated":"2023-10-05T12:59:59Z","snapshot_observed_at":"2026-07-06T16:01:11.052152Z","submitted_at":"2023-08-01T10:31:36Z","title":"SelfCheck: Using LLMs to Zero-Shot Check Their Own Step-by-Step Reasoning","version":3},"cited_work":{"arxiv_id":"2308.00436","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2308.00436","snapshot_observed_at":"2026-06-28T22:32:44.141882Z","title":"arXiv preprint arXiv:2308.00436 , year=","venue":null,"work_id":"1bd8771e-344a-4981-be63-3a4e84fd2df5","year":2023},"citing_paper":{"arxiv_id":"2606.00726","last_updated":"2026-07-10T01:15:34Z","snapshot_observed_at":"2026-08-02T05:37:27.284595Z","submitted_at":"2026-05-30T13:38:06Z","title":"Latent Reward Steering: An Adaptive Inference-Time Framework that Implicitly Promotes Cognitive Behaviors in Reasoning LLMs","version":1},"reference_index":67,"source":"arxiv_source","source_observed_at":"2026-06-28T18:49:56.917505Z"},"links":{"cited_paper":"/paper/2308.00436","citing_paper":"/paper/2606.00726"},"observation_digest":"sha256:452a842002183252017521d7aeba3f8004d6af76c604431fed5809a9b1c4d873","observation_id":"cb6e3098-75a2-4ff6-ac78-20a386c36644","resolution":{"observed_at":"2026-06-28T19:52:35.482916Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2308.00436","last_updated":"2023-10-05T12:59:59Z","snapshot_observed_at":"2026-07-06T16:01:11.052152Z","submitted_at":"2023-08-01T10:31:36Z","title":"SelfCheck: Using LLMs to Zero-Shot Check Their Own Step-by-Step Reasoning","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2308.00436","snapshot_observed_at":"2026-07-13T07:46:18.094867Z","title":"David Rein, Betty Li Hou, Asa Cooper Stickland, Jack- son Petty, Richard Yuanzhe Pang, Julien Dirani, Ju- lian Michael, and Samuel R Bowman","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2606.00726","last_updated":"2026-07-10T01:15:34Z","snapshot_observed_at":"2026-08-02T05:37:27.284595Z","submitted_at":"2026-05-30T13:38:06Z","title":"Latent Reward Steering: An Adaptive Inference-Time Framework that Implicitly Promotes Cognitive Behaviors in Reasoning LLMs","version":2},"reference_index":1,"source":"pdf_text","source_observed_at":"2026-07-13T07:46:18.094867Z"},"links":{"cited_paper":"/paper/2308.00436","citing_paper":"/paper/2606.00726"},"observation_digest":"sha256:70dc9da5c00bddbada525fb5dad9bf063cfb2ec2c04e79c68acf529f1091d85a","observation_id":"94c17467-d6c8-48e8-8adb-279432afb72f","resolution":{"observed_at":"2026-07-13T07:46:18.094867Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2308.00436","last_updated":"2023-10-05T12:59:59Z","snapshot_observed_at":"2026-07-06T16:01:11.052152Z","submitted_at":"2023-08-01T10:31:36Z","title":"SelfCheck: Using LLMs to Zero-Shot Check Their Own Step-by-Step Reasoning","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2308.00436","snapshot_observed_at":"2026-07-12T01:50:59.184754Z","title":"arXiv preprint arXiv:2308.00436 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.03530","last_updated":"2026-07-03T17:59:58Z","snapshot_observed_at":"2026-08-04T18:44:44.436706Z","submitted_at":"2026-07-03T17:59:58Z","title":"MentalThink: Shaping Thoughts in Mental SVG World","version":1},"reference_index":214,"source":"arxiv_source","source_observed_at":"2026-07-12T01:50:59.184754Z"},"links":{"cited_paper":"/paper/2308.00436","citing_paper":"/paper/2607.03530"},"observation_digest":"sha256:7646ba8c3bf92f1a9dfa83c5235ddad417b9cab28d4e58ef22d2a6b6a9f9b1ef","observation_id":"ffa6d392-98c8-4243-9a3b-637d26879f03","resolution":{"observed_at":"2026-07-12T01:50:59.184754Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2308.00436","last_updated":"2023-10-05T12:59:59Z","snapshot_observed_at":"2026-07-06T16:01:11.052152Z","submitted_at":"2023-08-01T10:31:36Z","title":"SelfCheck: Using LLMs to Zero-Shot Check Their Own Step-by-Step Reasoning","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2308.00436","snapshot_observed_at":"2026-08-01T19:46:59.475358Z","title":"Selfcheck: Using LLMs to zero-shot check their own step-by-step reasoning, 2023","venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.16868","last_updated":"2026-07-18T16:14:08Z","snapshot_observed_at":"2026-08-03T13:48:36.507554Z","submitted_at":"2026-07-18T16:14:08Z","title":"Beyond Semantic Equivalence: Logical Graphs for LLM Uncertainty Quantification","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-01T19:46:59.475358Z"},"links":{"cited_paper":"/paper/2308.00436","citing_paper":"/paper/2607.16868"},"observation_digest":"sha256:2cc65c38d29d8c076445dc23594060070d57390dcf0a2063a1215fb5ff49ee23","observation_id":"e255b79c-4dc2-48a3-ae0b-a520e5f64046","resolution":{"observed_at":"2026-08-01T19:46:59.475358Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2308.00436","last_updated":"2023-10-05T12:59:59Z","snapshot_observed_at":"2026-07-06T16:01:11.052152Z","submitted_at":"2023-08-01T10:31:36Z","title":"SelfCheck: Using LLMs to Zero-Shot Check Their Own Step-by-Step Reasoning","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2308.00436","snapshot_observed_at":"2026-08-02T12:15:24.501118Z","title":null,"venue":null,"work_id":null,"year":2023},"citing_paper":{"arxiv_id":"2607.18271","last_updated":"2026-06-04T21:20:24Z","snapshot_observed_at":"2026-08-02T19:08:03.408579Z","submitted_at":"2026-06-04T21:20:24Z","title":"Using LLMs for Explainable, Data-Driven Insight Generation from Time Series","version":1},"reference_index":29,"source":"pdf_text","source_observed_at":"2026-08-02T12:15:24.501118Z"},"links":{"cited_paper":"/paper/2308.00436","citing_paper":"/paper/2607.18271"},"observation_digest":"sha256:1ee56fdb08ac80cd539bd595f2da159cf3157b1c6a42a9f776ff166ba6e6445f","observation_id":"6fdd39e5-693e-4429-b245-b151e34af687","resolution":{"observed_at":"2026-08-02T12:15:24.501118Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2308.00436/citation-record","integrity":"/paper/2308.00436/integrity","json":"/paper/2308.00436/citation-record.json","paper":"/paper/2308.00436"},"outbound":[],"paper":{"arxiv_id":"2308.00436","last_updated":"2023-10-05T12:59:59Z","latest_version":3,"primary_category":"cs.AI","snapshot_observed_at":"2026-07-06T16:01:11.052152Z","submitted_at":"2023-08-01T10:31:36Z","title":"SelfCheck: Using LLMs to Zero-Shot Check Their Own Step-by-Step Reasoning"},"reference_resolution":{"displayed":0,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":0,"verified_exact":0,"verified_fuzzy":0},"total_outbound_references":0},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-05T06:32:48.257954+00:00","source":"crossref"},{"observed_at":"2026-08-05T06:32:44.755628+00:00","source":"retraction_watch"}],"thesis":"As of 5 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 16 inbound Pith citation observations for arXiv:2308.00436."}