{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2023:ES4XM7VK4WOA3DPNV5Y72OZOL6","short_pith_number":"pith:ES4XM7VK","schema_version":"1.0","canonical_sha256":"24b9767eaae59c0d8dedaf71fd3b2e5fb42d1745debcb0f854bb68ec97a286b2","source":{"kind":"arxiv","id":"2311.13982","version":1},"attestation_state":"computed","paper":{"title":"Probabilistic Tree-of-thought Reasoning for Answering Knowledge-intensive Complex Questions","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CL","authors_text":"Jiajie Zhang, Jiaxin Shi, Juanzi Li, Lei Hou, Qi Tian, Shulin Cao, Xin Lv, Zijun Yao","submitted_at":"2023-11-23T12:52:37Z","abstract_excerpt":"Large language models (LLMs) are capable of answering knowledge-intensive complex questions with chain-of-thought (CoT) reasoning. However, they tend to generate factually incorrect reasoning steps when the required knowledge is not available or up-to-date in models' parameters. Recent works turn to retrieving external knowledge to augment CoT reasoning. Despite being promising, these chain-based methods suffer from: 1) Negative retrieval. Unnecessary or incorrect retrieval may mislead the reasoning; 2) Limited sight. Lacking the ability to look backward or forward, a local error in one step w"},"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":"2311.13982","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2023-11-23T12:52:37Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"47dcad9d6b5866fe797a0b231844d1ca8975051e3a6fc3c98f98e4ef8d642847","abstract_canon_sha256":"f11017ece73811ac89db089c52d6856b77794815240a5a989eda8ae26ca2fdff"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T07:16:11.832920Z","signature_b64":"vvge+zmrTqhmGEhpZOMZgtx6YbqzpV0uIzR3q40Gt6bU1kvSavQvHJgGZm1mHSubSg2/zzH5t8/dRtKiH0NkCg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"24b9767eaae59c0d8dedaf71fd3b2e5fb42d1745debcb0f854bb68ec97a286b2","last_reissued_at":"2026-07-05T07:16:11.832473Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T07:16:11.832473Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Probabilistic Tree-of-thought Reasoning for Answering Knowledge-intensive Complex Questions","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CL","authors_text":"Jiajie Zhang, Jiaxin Shi, Juanzi Li, Lei Hou, Qi Tian, Shulin Cao, Xin Lv, Zijun Yao","submitted_at":"2023-11-23T12:52:37Z","abstract_excerpt":"Large language models (LLMs) are capable of answering knowledge-intensive complex questions with chain-of-thought (CoT) reasoning. However, they tend to generate factually incorrect reasoning steps when the required knowledge is not available or up-to-date in models' parameters. Recent works turn to retrieving external knowledge to augment CoT reasoning. Despite being promising, these chain-based methods suffer from: 1) Negative retrieval. Unnecessary or incorrect retrieval may mislead the reasoning; 2) Limited sight. Lacking the ability to look backward or forward, a local error in one step w"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2311.13982","kind":"arxiv","version":1},"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/2311.13982/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":"2311.13982","created_at":"2026-07-05T07:16:11.832532+00:00"},{"alias_kind":"arxiv_version","alias_value":"2311.13982v1","created_at":"2026-07-05T07:16:11.832532+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2311.13982","created_at":"2026-07-05T07:16:11.832532+00:00"},{"alias_kind":"pith_short_12","alias_value":"ES4XM7VK4WOA","created_at":"2026-07-05T07:16:11.832532+00:00"},{"alias_kind":"pith_short_16","alias_value":"ES4XM7VK4WOA3DPN","created_at":"2026-07-05T07:16:11.832532+00:00"},{"alias_kind":"pith_short_8","alias_value":"ES4XM7VK","created_at":"2026-07-05T07:16:11.832532+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/ES4XM7VK4WOA3DPNV5Y72OZOL6","json":"https://pith.science/pith/ES4XM7VK4WOA3DPNV5Y72OZOL6.json","graph_json":"https://pith.science/api/pith-number/ES4XM7VK4WOA3DPNV5Y72OZOL6/graph.json","events_json":"https://pith.science/api/pith-number/ES4XM7VK4WOA3DPNV5Y72OZOL6/events.json","paper":"https://pith.science/paper/ES4XM7VK"},"agent_actions":{"view_html":"https://pith.science/pith/ES4XM7VK4WOA3DPNV5Y72OZOL6","download_json":"https://pith.science/pith/ES4XM7VK4WOA3DPNV5Y72OZOL6.json","view_paper":"https://pith.science/paper/ES4XM7VK","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2311.13982&json=true","fetch_graph":"https://pith.science/api/pith-number/ES4XM7VK4WOA3DPNV5Y72OZOL6/graph.json","fetch_events":"https://pith.science/api/pith-number/ES4XM7VK4WOA3DPNV5Y72OZOL6/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/ES4XM7VK4WOA3DPNV5Y72OZOL6/action/timestamp_anchor","attest_storage":"https://pith.science/pith/ES4XM7VK4WOA3DPNV5Y72OZOL6/action/storage_attestation","attest_author":"https://pith.science/pith/ES4XM7VK4WOA3DPNV5Y72OZOL6/action/author_attestation","sign_citation":"https://pith.science/pith/ES4XM7VK4WOA3DPNV5Y72OZOL6/action/citation_signature","submit_replication":"https://pith.science/pith/ES4XM7VK4WOA3DPNV5Y72OZOL6/action/replication_record"}},"created_at":"2026-07-05T07:16:11.832532+00:00","updated_at":"2026-07-05T07:16:11.832532+00:00"}