{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2025:5PH3PKSWIRCSQWQ6QWYEKXCFWR","short_pith_number":"pith:5PH3PKSW","schema_version":"1.0","canonical_sha256":"ebcfb7aa564445285a1e85b0455c45b446b5bc8bb116fdbfbadb9c878be751e4","source":{"kind":"arxiv","id":"2501.17186","version":2},"attestation_state":"computed","paper":{"title":"Complete Chess Games Enable LLM Become A Chess Master","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":["cs.CL","cs.LG"],"primary_cat":"cs.AI","authors_text":"Haolong Li, Kedi Chen, Shaohui Lin, Xintian Han, Yinqi Zhang","submitted_at":"2025-01-26T09:43:39Z","abstract_excerpt":"Large language models (LLM) have shown remarkable abilities in text generation, question answering, language translation, reasoning and many other tasks. It continues to advance rapidly and is becoming increasingly influential in various fields, from technology and business to education and entertainment. Despite LLM's success in multiple areas, its ability to play abstract games, such as chess, is underexplored. Chess-playing requires the language models to output legal and reasonable moves from textual inputs. Here, we propose the Large language model ChessLLM to play full chess games. We tr"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2501.17186","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.AI","submitted_at":"2025-01-26T09:43:39Z","cross_cats_sorted":["cs.CL","cs.LG"],"title_canon_sha256":"d36aa7ed3bf77ad6fb41b68d270aea5479eff034aed05d668045f2b8e34e455f","abstract_canon_sha256":"cf1ff1d95d55a150c2ff7bca79c4e319b824f9e33d3a633dc461e7f5a424eb48"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T10:07:03.030573Z","signature_b64":"8fKbtZZFcE1XCxWhsoycfcRTNtKU5AjO2r0EYrYqedPSW+D9g5F0g0MthEvO07Dgp6n7gqpJ78MLwV56ieThCA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"ebcfb7aa564445285a1e85b0455c45b446b5bc8bb116fdbfbadb9c878be751e4","last_reissued_at":"2026-07-05T10:07:03.030095Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T10:07:03.030095Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Complete Chess Games Enable LLM Become A Chess Master","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":["cs.CL","cs.LG"],"primary_cat":"cs.AI","authors_text":"Haolong Li, Kedi Chen, Shaohui Lin, Xintian Han, Yinqi Zhang","submitted_at":"2025-01-26T09:43:39Z","abstract_excerpt":"Large language models (LLM) have shown remarkable abilities in text generation, question answering, language translation, reasoning and many other tasks. It continues to advance rapidly and is becoming increasingly influential in various fields, from technology and business to education and entertainment. Despite LLM's success in multiple areas, its ability to play abstract games, such as chess, is underexplored. Chess-playing requires the language models to output legal and reasonable moves from textual inputs. Here, we propose the Large language model ChessLLM to play full chess games. We tr"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2501.17186","kind":"arxiv","version":2},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2501.17186/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"},"aliases":[{"alias_kind":"arxiv","alias_value":"2501.17186","created_at":"2026-07-05T10:07:03.030153+00:00"},{"alias_kind":"arxiv_version","alias_value":"2501.17186v2","created_at":"2026-07-05T10:07:03.030153+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2501.17186","created_at":"2026-07-05T10:07:03.030153+00:00"},{"alias_kind":"pith_short_12","alias_value":"5PH3PKSWIRCS","created_at":"2026-07-05T10:07:03.030153+00:00"},{"alias_kind":"pith_short_16","alias_value":"5PH3PKSWIRCSQWQ6","created_at":"2026-07-05T10:07:03.030153+00:00"},{"alias_kind":"pith_short_8","alias_value":"5PH3PKSW","created_at":"2026-07-05T10:07:03.030153+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":2,"internal_anchor_count":0,"sample":[{"citing_arxiv_id":"2605.09965","citing_title":"Towards Generalist Game Players: An Investigation of Foundation Models in the Game Multiverse","ref_index":219,"is_internal_anchor":false},{"citing_arxiv_id":"2605.09965","citing_title":"Towards Generalist Game Players: An Investigation of Foundation Models in the Game Multiverse","ref_index":219,"is_internal_anchor":false}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/5PH3PKSWIRCSQWQ6QWYEKXCFWR","json":"https://pith.science/pith/5PH3PKSWIRCSQWQ6QWYEKXCFWR.json","graph_json":"https://pith.science/api/pith-number/5PH3PKSWIRCSQWQ6QWYEKXCFWR/graph.json","events_json":"https://pith.science/api/pith-number/5PH3PKSWIRCSQWQ6QWYEKXCFWR/events.json","paper":"https://pith.science/paper/5PH3PKSW"},"agent_actions":{"view_html":"https://pith.science/pith/5PH3PKSWIRCSQWQ6QWYEKXCFWR","download_json":"https://pith.science/pith/5PH3PKSWIRCSQWQ6QWYEKXCFWR.json","view_paper":"https://pith.science/paper/5PH3PKSW","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2501.17186&json=true","fetch_graph":"https://pith.science/api/pith-number/5PH3PKSWIRCSQWQ6QWYEKXCFWR/graph.json","fetch_events":"https://pith.science/api/pith-number/5PH3PKSWIRCSQWQ6QWYEKXCFWR/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/5PH3PKSWIRCSQWQ6QWYEKXCFWR/action/timestamp_anchor","attest_storage":"https://pith.science/pith/5PH3PKSWIRCSQWQ6QWYEKXCFWR/action/storage_attestation","attest_author":"https://pith.science/pith/5PH3PKSWIRCSQWQ6QWYEKXCFWR/action/author_attestation","sign_citation":"https://pith.science/pith/5PH3PKSWIRCSQWQ6QWYEKXCFWR/action/citation_signature","submit_replication":"https://pith.science/pith/5PH3PKSWIRCSQWQ6QWYEKXCFWR/action/replication_record"}},"created_at":"2026-07-05T10:07:03.030153+00:00","updated_at":"2026-07-05T10:07:03.030153+00:00"}