{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2023:WUJATENZ4CNLPBWNDUPBRX735C","short_pith_number":"pith:WUJATENZ","schema_version":"1.0","canonical_sha256":"b5120991b9e09ab786cd1d1e18dffbe8b5f792bb020cc10b11f97679de151e09","source":{"kind":"arxiv","id":"2310.07582","version":2},"attestation_state":"computed","paper":{"title":"Linear Latent World Models in Simple Transformers: A Case Study on Othello-GPT","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.LG","authors_text":"Dean S. Hazineh, Jeffery Chiu, Zechen Zhang","submitted_at":"2023-10-11T15:20:07Z","abstract_excerpt":"Foundation models exhibit significant capabilities in decision-making and logical deductions. Nonetheless, a continuing discourse persists regarding their genuine understanding of the world as opposed to mere stochastic mimicry. This paper meticulously examines a simple transformer trained for Othello, extending prior research to enhance comprehension of the emergent world model of Othello-GPT. The investigation reveals that Othello-GPT encapsulates a linear representation of opposing pieces, a factor that causally steers its decision-making process. This paper further elucidates the interplay"},"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":"2310.07582","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2023-10-11T15:20:07Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"dee41e33ad57e07792ab16c205a817fd86d2359f7cfe83bfc197798ddcd6a412","abstract_canon_sha256":"6318b89da8f012afdd1cad4dc26ae4398b2f72e91e34ec001c0b3ac6edcd9321"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T07:04:00.926231Z","signature_b64":"wXlzzR0TcaQtfeEUqhzLWvbjsM8fu3uY4FbhqdXpEhPndDnqgpD2hNyI3QvAdoKoag6DzsNYJ3S+QazdIOt/Bg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"b5120991b9e09ab786cd1d1e18dffbe8b5f792bb020cc10b11f97679de151e09","last_reissued_at":"2026-07-05T07:04:00.925755Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T07:04:00.925755Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Linear Latent World Models in Simple Transformers: A Case Study on Othello-GPT","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.LG","authors_text":"Dean S. Hazineh, Jeffery Chiu, Zechen Zhang","submitted_at":"2023-10-11T15:20:07Z","abstract_excerpt":"Foundation models exhibit significant capabilities in decision-making and logical deductions. Nonetheless, a continuing discourse persists regarding their genuine understanding of the world as opposed to mere stochastic mimicry. This paper meticulously examines a simple transformer trained for Othello, extending prior research to enhance comprehension of the emergent world model of Othello-GPT. The investigation reveals that Othello-GPT encapsulates a linear representation of opposing pieces, a factor that causally steers its decision-making process. This paper further elucidates the interplay"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2310.07582","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/2310.07582/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":"2310.07582","created_at":"2026-07-05T07:04:00.925819+00:00"},{"alias_kind":"arxiv_version","alias_value":"2310.07582v2","created_at":"2026-07-05T07:04:00.925819+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2310.07582","created_at":"2026-07-05T07:04:00.925819+00:00"},{"alias_kind":"pith_short_12","alias_value":"WUJATENZ4CNL","created_at":"2026-07-05T07:04:00.925819+00:00"},{"alias_kind":"pith_short_16","alias_value":"WUJATENZ4CNLPBWN","created_at":"2026-07-05T07:04:00.925819+00:00"},{"alias_kind":"pith_short_8","alias_value":"WUJATENZ","created_at":"2026-07-05T07:04:00.925819+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":1,"internal_anchor_count":0,"sample":[{"citing_arxiv_id":"2606.13607","citing_title":"Reasoning as Pattern Matching: Shared Mechanisms in Human and LLM Everyday Reasoning","ref_index":7,"is_internal_anchor":false}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/WUJATENZ4CNLPBWNDUPBRX735C","json":"https://pith.science/pith/WUJATENZ4CNLPBWNDUPBRX735C.json","graph_json":"https://pith.science/api/pith-number/WUJATENZ4CNLPBWNDUPBRX735C/graph.json","events_json":"https://pith.science/api/pith-number/WUJATENZ4CNLPBWNDUPBRX735C/events.json","paper":"https://pith.science/paper/WUJATENZ"},"agent_actions":{"view_html":"https://pith.science/pith/WUJATENZ4CNLPBWNDUPBRX735C","download_json":"https://pith.science/pith/WUJATENZ4CNLPBWNDUPBRX735C.json","view_paper":"https://pith.science/paper/WUJATENZ","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2310.07582&json=true","fetch_graph":"https://pith.science/api/pith-number/WUJATENZ4CNLPBWNDUPBRX735C/graph.json","fetch_events":"https://pith.science/api/pith-number/WUJATENZ4CNLPBWNDUPBRX735C/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/WUJATENZ4CNLPBWNDUPBRX735C/action/timestamp_anchor","attest_storage":"https://pith.science/pith/WUJATENZ4CNLPBWNDUPBRX735C/action/storage_attestation","attest_author":"https://pith.science/pith/WUJATENZ4CNLPBWNDUPBRX735C/action/author_attestation","sign_citation":"https://pith.science/pith/WUJATENZ4CNLPBWNDUPBRX735C/action/citation_signature","submit_replication":"https://pith.science/pith/WUJATENZ4CNLPBWNDUPBRX735C/action/replication_record"}},"created_at":"2026-07-05T07:04:00.925819+00:00","updated_at":"2026-07-05T07:04:00.925819+00:00"}