{"as_of":"2026-08-09T22:47:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:58c9808c7f8665d8fa5b17875b65bb2a61d78a5f87fb7e27ca0cab2dcd75cd6c","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":11,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":11,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-09T06:31:02.800959+00:00","state":"measured"},{"denominator":11,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":11,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-08T13:48:54.841122Z","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":"2026-07-02T01:46:26.448109Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"2412.12119","last_updated":"2025-05-23T01:35:09Z","snapshot_observed_at":"2026-08-05T22:48:20.543785Z","submitted_at":"2024-12-02T18:56:51Z","title":"Mastering Board Games by External and Internal Planning with Language Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2412.12119","snapshot_observed_at":"2026-08-08T13:48:54.841122Z","title":null,"venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2502.07128","last_updated":"2025-09-09T16:20:01Z","snapshot_observed_at":"2026-08-08T13:41:08.095949Z","submitted_at":"2025-02-10T23:47:35Z","title":"Cardiverse: Harnessing LLMs for Novel Card Game Prototyping","version":2},"reference_index":2024,"source":"pdf_text","source_observed_at":"2026-08-08T13:48:54.841122Z"},"links":{"cited_paper":"/paper/2412.12119","citing_paper":"/paper/2502.07128"},"observation_digest":"sha256:374e5d479d45510d63e5e84b602ca5d4fc883f971e2214828329e72248d4a9e4","observation_id":"7eebda9c-e80c-4f4f-b89d-00f4a0e15cd9","resolution":{"observed_at":"2026-08-08T13:48:54.841122Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2412.12119","last_updated":"2025-05-23T01:35:09Z","snapshot_observed_at":"2026-08-05T22:48:20.543785Z","submitted_at":"2024-12-02T18:56:51Z","title":"Mastering Board Games by External and Internal Planning with Language Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2412.12119","snapshot_observed_at":"2026-08-06T15:48:11.995181Z","title":"arXiv preprint arXiv:2412.12119 (2024)","venue":null,"work_id":null,"year":2024},"citing_paper":{"arxiv_id":"2507.14906","last_updated":"2025-07-20T10:38:56Z","snapshot_observed_at":"2026-08-08T17:27:28.136805Z","submitted_at":"2025-07-20T10:38:56Z","title":"Feedback-Induced Performance Decline in LLM-Based Decision-Making","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-08-06T15:48:11.995181Z"},"links":{"cited_paper":"/paper/2412.12119","citing_paper":"/paper/2507.14906"},"observation_digest":"sha256:f310485effccd07342b3676f5913958a0fd56e433d8dd59b95b3e1d64f1dabcc","observation_id":"d9c546cc-cd40-4fdc-bc84-29d75493298c","resolution":{"observed_at":"2026-08-06T15:48:11.995181Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"2412.12119","last_updated":"2025-05-23T01:35:09Z","snapshot_observed_at":"2026-08-05T22:48:20.543785Z","submitted_at":"2024-12-02T18:56:51Z","title":"Mastering Board Games by External and Internal Planning with Language Models","version":3},"cited_work":{"arxiv_id":"2412.12119","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2412.12119","snapshot_observed_at":"2026-07-02T01:46:26.448109Z","title":"Mastering board games by external and internal planning with language models","venue":null,"work_id":"6b9b02fb-0574-497e-bde9-3237d3cbf4fa","year":2024},"citing_paper":{"arxiv_id":"2601.12538","last_updated":"2026-01-18T18:58:23Z","snapshot_observed_at":"2026-08-04T22:42:23.171653Z","submitted_at":"2026-01-18T18:58:23Z","title":"Agentic Reasoning for Large Language Models","version":1},"reference_index":122,"source":"pdf_text","source_observed_at":"2026-05-17T15:14:25.558878Z"},"links":{"cited_paper":"/paper/2412.12119","citing_paper":"/paper/2601.12538"},"observation_digest":"sha256:490bcbe2ae78853495f35c79d86d80338b324e7522f6bb4fe014f9cdece829a7","observation_id":"50b10552-c870-437d-bb4b-843b0f251a20","resolution":{"observed_at":"2026-05-17T15:14:26.062550Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.12119","last_updated":"2025-05-23T01:35:09Z","snapshot_observed_at":"2026-08-05T22:48:20.543785Z","submitted_at":"2024-12-02T18:56:51Z","title":"Mastering Board Games by External and Internal Planning with Language Models","version":3},"cited_work":{"arxiv_id":"2412.12119","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2412.12119","snapshot_observed_at":"2026-07-02T01:46:26.448109Z","title":"Mastering board games by external and internal planning with language models","venue":null,"work_id":"6b9b02fb-0574-497e-bde9-3237d3cbf4fa","year":2024},"citing_paper":{"arxiv_id":"2605.06840","last_updated":"2026-05-22T00:29:09Z","snapshot_observed_at":"2026-08-03T21:39:56.998797Z","submitted_at":"2026-05-07T18:45:46Z","title":"Extracting Search Trees from LLM Reasoning Traces Reveals Myopic Planning","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-05-11T00:52:59.406190Z"},"links":{"cited_paper":"/paper/2412.12119","citing_paper":"/paper/2605.06840"},"observation_digest":"sha256:8cdfcbab6fddca0337121d8cf37de7782ab29e02a862037a1cf9de1fcf9789d0","observation_id":"6b513a22-c799-4c6d-ae97-33fd960fa329","resolution":{"observed_at":"2026-05-11T05:05:56.674420Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.12119","last_updated":"2025-05-23T01:35:09Z","snapshot_observed_at":"2026-08-05T22:48:20.543785Z","submitted_at":"2024-12-02T18:56:51Z","title":"Mastering Board Games by External and Internal Planning with Language Models","version":3},"cited_work":{"arxiv_id":"2412.12119","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2412.12119","snapshot_observed_at":"2026-07-02T01:46:26.448109Z","title":"Mastering board games by external and internal planning with language models","venue":null,"work_id":"6b9b02fb-0574-497e-bde9-3237d3cbf4fa","year":2024},"citing_paper":{"arxiv_id":"2605.06840","last_updated":"2026-05-22T00:29:09Z","snapshot_observed_at":"2026-08-03T21:39:56.998797Z","submitted_at":"2026-05-07T18:45:46Z","title":"Extracting Search Trees from LLM Reasoning Traces Reveals Myopic Planning","version":2},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-05-12T02:23:55.323250Z"},"links":{"cited_paper":"/paper/2412.12119","citing_paper":"/paper/2605.06840"},"observation_digest":"sha256:a3a24fec9205ec94b2d38590fd8731ccd7a4c3bd9c436bd0c3415a059068011f","observation_id":"5fbb47d9-d8f0-4f2c-8c09-8cd1b99fbdc7","resolution":{"observed_at":"2026-05-12T07:41:28.096652Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.12119","last_updated":"2025-05-23T01:35:09Z","snapshot_observed_at":"2026-08-05T22:48:20.543785Z","submitted_at":"2024-12-02T18:56:51Z","title":"Mastering Board Games by External and Internal Planning with Language Models","version":3},"cited_work":{"arxiv_id":"2412.12119","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2412.12119","snapshot_observed_at":"2026-07-02T01:46:26.448109Z","title":"Mastering board games by external and internal planning with language models","venue":null,"work_id":"6b9b02fb-0574-497e-bde9-3237d3cbf4fa","year":2024},"citing_paper":{"arxiv_id":"2605.06840","last_updated":"2026-05-22T00:29:09Z","snapshot_observed_at":"2026-08-03T21:39:56.998797Z","submitted_at":"2026-05-07T18:45:46Z","title":"Extracting Search Trees from LLM Reasoning Traces Reveals Myopic Planning","version":3},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-05-13T06:21:00.353334Z"},"links":{"cited_paper":"/paper/2412.12119","citing_paper":"/paper/2605.06840"},"observation_digest":"sha256:615bd05d1a7177f9596347c563414f50a70243358127aa369d0e87e8de9033b0","observation_id":"3843746e-35d5-4404-aa4f-df1ef8125a74","resolution":{"observed_at":"2026-05-13T06:22:23.222052Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.12119","last_updated":"2025-05-23T01:35:09Z","snapshot_observed_at":"2026-08-05T22:48:20.543785Z","submitted_at":"2024-12-02T18:56:51Z","title":"Mastering Board Games by External and Internal Planning with Language Models","version":3},"cited_work":{"arxiv_id":"2412.12119","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2412.12119","snapshot_observed_at":"2026-07-02T01:46:26.448109Z","title":"Mastering board games by external and internal planning with language models","venue":null,"work_id":"6b9b02fb-0574-497e-bde9-3237d3cbf4fa","year":2024},"citing_paper":{"arxiv_id":"2605.06840","last_updated":"2026-05-22T00:29:09Z","snapshot_observed_at":"2026-08-03T21:39:56.998797Z","submitted_at":"2026-05-07T18:45:46Z","title":"Extracting Search Trees from LLM Reasoning Traces Reveals Myopic Planning","version":4},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-05-14T20:55:31.770238Z"},"links":{"cited_paper":"/paper/2412.12119","citing_paper":"/paper/2605.06840"},"observation_digest":"sha256:da6ea7349a698fa081a4025416a9bdeb1b92d9f8c8d620ec6374a2a2c58ac8bd","observation_id":"3289dd3f-d7bb-4f0b-9fe0-78ad60644f6c","resolution":{"observed_at":"2026-05-14T20:59:27.836639Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.12119","last_updated":"2025-05-23T01:35:09Z","snapshot_observed_at":"2026-08-05T22:48:20.543785Z","submitted_at":"2024-12-02T18:56:51Z","title":"Mastering Board Games by External and Internal Planning with Language Models","version":3},"cited_work":{"arxiv_id":"2412.12119","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2412.12119","snapshot_observed_at":"2026-07-02T01:46:26.448109Z","title":"Mastering board games by external and internal planning with language models","venue":null,"work_id":"6b9b02fb-0574-497e-bde9-3237d3cbf4fa","year":2024},"citing_paper":{"arxiv_id":"2605.06840","last_updated":"2026-05-22T00:29:09Z","snapshot_observed_at":"2026-08-03T21:39:56.998797Z","submitted_at":"2026-05-07T18:45:46Z","title":"Extracting Search Trees from LLM Reasoning Traces Reveals Myopic Planning","version":5},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-05-25T05:57:58.487109Z"},"links":{"cited_paper":"/paper/2412.12119","citing_paper":"/paper/2605.06840"},"observation_digest":"sha256:1ebbef665d68c73bca47cc938544a857cdd244e5517909e8b0697a586a72465d","observation_id":"b8502c47-c660-4309-a428-8fda934816e2","resolution":{"observed_at":"2026-05-25T06:00:23.426902Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.12119","last_updated":"2025-05-23T01:35:09Z","snapshot_observed_at":"2026-08-05T22:48:20.543785Z","submitted_at":"2024-12-02T18:56:51Z","title":"Mastering Board Games by External and Internal Planning with Language Models","version":3},"cited_work":{"arxiv_id":"2412.12119","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2412.12119","snapshot_observed_at":"2026-07-02T01:46:26.448109Z","title":"Mastering board games by external and internal planning with language models","venue":null,"work_id":"6b9b02fb-0574-497e-bde9-3237d3cbf4fa","year":2024},"citing_paper":{"arxiv_id":"2605.24375","last_updated":"2026-05-23T03:30:36Z","snapshot_observed_at":"2026-08-04T17:22:32.357745Z","submitted_at":"2026-05-23T03:30:36Z","title":"Distilling Game Code World Model Generation into Lightweight Large Language Models","version":1},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-06-30T13:58:37.956333Z"},"links":{"cited_paper":"/paper/2412.12119","citing_paper":"/paper/2605.24375"},"observation_digest":"sha256:7df3df56ee74de6672e6d4522379a20458d9598190ce7d936827349c8f65b6d7","observation_id":"203b92e4-930e-4ed2-a816-b6209c369ece","resolution":{"observed_at":"2026-06-30T14:04:44.639710Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.12119","last_updated":"2025-05-23T01:35:09Z","snapshot_observed_at":"2026-08-05T22:48:20.543785Z","submitted_at":"2024-12-02T18:56:51Z","title":"Mastering Board Games by External and Internal Planning with Language Models","version":3},"cited_work":{"arxiv_id":"2412.12119","doi":null,"metadata_source":"arxiv_reference","pith_arxiv_id":"2412.12119","snapshot_observed_at":"2026-07-02T01:46:26.448109Z","title":"Mastering board games by external and internal planning with language models","venue":null,"work_id":"6b9b02fb-0574-497e-bde9-3237d3cbf4fa","year":2024},"citing_paper":{"arxiv_id":"2606.03685","last_updated":"2026-06-02T14:09:16Z","snapshot_observed_at":"2026-08-07T10:48:20.979251Z","submitted_at":"2026-06-02T14:09:16Z","title":"A Close Look At World Model Recovery In Supervised Fine-Tuned LLM Planners","version":1},"reference_index":21,"source":"pdf_text","source_observed_at":"2026-06-28T11:36:14.896698Z"},"links":{"cited_paper":"/paper/2412.12119","citing_paper":"/paper/2606.03685"},"observation_digest":"sha256:b926b71f42a3f1e65b692b169e6fe965124792277f6f675e7774f89521d3920a","observation_id":"663e0c4a-ef9b-43ac-8b03-4ec83f585239","resolution":{"observed_at":"2026-07-02T01:46:26.450915Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"2412.12119","last_updated":"2025-05-23T01:35:09Z","snapshot_observed_at":"2026-08-05T22:48:20.543785Z","submitted_at":"2024-12-02T18:56:51Z","title":"Mastering Board Games by External and Internal Planning with Language Models","version":3},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"2412.12119","snapshot_observed_at":"2026-07-14T05:17:06.012512Z","title":"arXiv preprint arXiv:2412.12119 , year=","venue":null,"work_id":null,"year":null},"citing_paper":{"arxiv_id":"2607.11486","last_updated":"2026-07-13T12:40:10Z","snapshot_observed_at":"2026-08-06T05:02:12.829809Z","submitted_at":"2026-07-13T12:40:10Z","title":"Communicating Chess Strategies in Natural Language","version":1},"reference_index":9,"source":"arxiv_source","source_observed_at":"2026-07-14T05:17:06.012512Z"},"links":{"cited_paper":"/paper/2412.12119","citing_paper":"/paper/2607.11486"},"observation_digest":"sha256:4a80a4eb19a4f6a1214a3e79fb5942fee6da9acede46272327492e3ea41caabf","observation_id":"755f593d-2aa6-4bb9-8315-c506baed23b2","resolution":{"observed_at":"2026-07-14T05:17:06.012512Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/2412.12119/citation-record","integrity":"/paper/2412.12119/integrity","json":"/paper/2412.12119/citation-record.json","paper":"/paper/2412.12119"},"outbound":[],"paper":{"arxiv_id":"2412.12119","last_updated":"2025-05-23T01:35:09Z","latest_version":3,"primary_category":"cs.AI","snapshot_observed_at":"2026-08-05T22:48:20.543785Z","submitted_at":"2024-12-02T18:56:51Z","title":"Mastering Board Games by External and Internal Planning with Language Models"},"reference_resolution":{"displayed":0,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":0,"verified_exact":0,"verified_fuzzy":0},"total_outbound_references":0},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-09T06:31:02.800959+00:00","source":"crossref"},{"observed_at":"2026-08-09T06:30:57.326959+00:00","source":"retraction_watch"}],"thesis":"As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 11 inbound Pith citation observations for arXiv:2412.12119."}