{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:JBS5XQMAW7XFQEXREVE55V6LJI","short_pith_number":"pith:JBS5XQMA","canonical_record":{"source":{"id":"2412.13292","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-12-17T19:45:53Z","cross_cats_sorted":[],"title_canon_sha256":"268f43c2566bc0656984ca9369cec41b025d90da6f3aa9a31ee65d0bef43d6e7","abstract_canon_sha256":"66199a307e617d7026d65387ad8e8f861f93f961bae5177b5a9b31b5acc324b7"},"schema_version":"1.0"},"canonical_sha256":"4865dbc180b7ee5812f12549ded7cb4a2a18534fb270e91dc15d9ef0b5914a0f","source":{"kind":"arxiv","id":"2412.13292","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2412.13292","created_at":"2026-07-05T10:46:59Z"},{"alias_kind":"arxiv_version","alias_value":"2412.13292v2","created_at":"2026-07-05T10:46:59Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2412.13292","created_at":"2026-07-05T10:46:59Z"},{"alias_kind":"pith_short_12","alias_value":"JBS5XQMAW7XF","created_at":"2026-07-05T10:46:59Z"},{"alias_kind":"pith_short_16","alias_value":"JBS5XQMAW7XFQEXR","created_at":"2026-07-05T10:46:59Z"},{"alias_kind":"pith_short_8","alias_value":"JBS5XQMA","created_at":"2026-07-05T10:46:59Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:JBS5XQMAW7XFQEXREVE55V6LJI","target":"record","payload":{"canonical_record":{"source":{"id":"2412.13292","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-12-17T19:45:53Z","cross_cats_sorted":[],"title_canon_sha256":"268f43c2566bc0656984ca9369cec41b025d90da6f3aa9a31ee65d0bef43d6e7","abstract_canon_sha256":"66199a307e617d7026d65387ad8e8f861f93f961bae5177b5a9b31b5acc324b7"},"schema_version":"1.0"},"canonical_sha256":"4865dbc180b7ee5812f12549ded7cb4a2a18534fb270e91dc15d9ef0b5914a0f","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T10:46:59.428206Z","signature_b64":"rtZ/wGIWgSnBz15mwc6+6t72N9F1rwEc7kbJRSjl4uts7hN/v8mNLPVgv0aDMqkbJFfUiynbdVAHbvw4aMnYDQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"4865dbc180b7ee5812f12549ded7cb4a2a18534fb270e91dc15d9ef0b5914a0f","last_reissued_at":"2026-07-05T10:46:59.427703Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T10:46:59.427703Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2412.13292","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T10:46:59Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"yWaBdfIB3pMb0/gSta5RN7h78Mx0oGEi6RVa5jbnT51bAAUOZxzEuGBwD+Jt9lxAY9txm2NpEO72nIU9MnAyBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-13T00:09:23.246686Z"},"content_sha256":"3e83519f31f5bf0c893f341d0f7f7ec76d2a756d3d333434da946cf8dba5e5d7","schema_version":"1.0","event_id":"sha256:3e83519f31f5bf0c893f341d0f7f7ec76d2a756d3d333434da946cf8dba5e5d7"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:JBS5XQMAW7XFQEXREVE55V6LJI","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Refining Answer Distributions for Improved Large Language Model Reasoning","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Didier Ch\\'etelat, Mark Coates, Soumyasundar Pal, Yingxue Zhang","submitted_at":"2024-12-17T19:45:53Z","abstract_excerpt":"Large Language Models (LLMs) have exhibited an impressive capability to perform reasoning tasks, especially if they are encouraged to generate a sequence of intermediate steps. Reasoning performance can be improved by suitably combining multiple LLM responses, generated either in parallel in a single query, or via sequential interactions with LLMs throughout the reasoning process. Existing strategies for combination, such as self-consistency and progressive-hint-prompting, make inefficient usage of the LLM responses. We present Refined Answer Distributions, a novel and principled algorithmic f"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2412.13292","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/2412.13292/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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T10:46:59Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"tJn+Cmnv5Ud7l9p/GQlRAm4y5QhWLxlItTBrZBxbx5xzwGr8ioOLT93AcRi1A5Wdh1YpDtGBWa7DG9FQr8atBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-13T00:09:23.296004Z"},"content_sha256":"91dc6981e6c50ab411ad8b6864996867cd3adf76b86c6933d035d5de32df1e88","schema_version":"1.0","event_id":"sha256:91dc6981e6c50ab411ad8b6864996867cd3adf76b86c6933d035d5de32df1e88"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/JBS5XQMAW7XFQEXREVE55V6LJI/bundle.json","state_url":"https://pith.science/pith/JBS5XQMAW7XFQEXREVE55V6LJI/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/JBS5XQMAW7XFQEXREVE55V6LJI/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-08-13T00:09:23Z","links":{"resolver":"https://pith.science/pith/JBS5XQMAW7XFQEXREVE55V6LJI","bundle":"https://pith.science/pith/JBS5XQMAW7XFQEXREVE55V6LJI/bundle.json","state":"https://pith.science/pith/JBS5XQMAW7XFQEXREVE55V6LJI/state.json","well_known_bundle":"https://pith.science/.well-known/pith/JBS5XQMAW7XFQEXREVE55V6LJI/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:JBS5XQMAW7XFQEXREVE55V6LJI","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"66199a307e617d7026d65387ad8e8f861f93f961bae5177b5a9b31b5acc324b7","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-12-17T19:45:53Z","title_canon_sha256":"268f43c2566bc0656984ca9369cec41b025d90da6f3aa9a31ee65d0bef43d6e7"},"schema_version":"1.0","source":{"id":"2412.13292","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2412.13292","created_at":"2026-07-05T10:46:59Z"},{"alias_kind":"arxiv_version","alias_value":"2412.13292v2","created_at":"2026-07-05T10:46:59Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2412.13292","created_at":"2026-07-05T10:46:59Z"},{"alias_kind":"pith_short_12","alias_value":"JBS5XQMAW7XF","created_at":"2026-07-05T10:46:59Z"},{"alias_kind":"pith_short_16","alias_value":"JBS5XQMAW7XFQEXR","created_at":"2026-07-05T10:46:59Z"},{"alias_kind":"pith_short_8","alias_value":"JBS5XQMA","created_at":"2026-07-05T10:46:59Z"}],"graph_snapshots":[{"event_id":"sha256:91dc6981e6c50ab411ad8b6864996867cd3adf76b86c6933d035d5de32df1e88","target":"graph","created_at":"2026-07-05T10:46:59Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2412.13292/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Large Language Models (LLMs) have exhibited an impressive capability to perform reasoning tasks, especially if they are encouraged to generate a sequence of intermediate steps. Reasoning performance can be improved by suitably combining multiple LLM responses, generated either in parallel in a single query, or via sequential interactions with LLMs throughout the reasoning process. Existing strategies for combination, such as self-consistency and progressive-hint-prompting, make inefficient usage of the LLM responses. We present Refined Answer Distributions, a novel and principled algorithmic f","authors_text":"Didier Ch\\'etelat, Mark Coates, Soumyasundar Pal, Yingxue Zhang","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-12-17T19:45:53Z","title":"Refining Answer Distributions for Improved Large Language Model Reasoning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2412.13292","kind":"arxiv","version":2},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:3e83519f31f5bf0c893f341d0f7f7ec76d2a756d3d333434da946cf8dba5e5d7","target":"record","created_at":"2026-07-05T10:46:59Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"66199a307e617d7026d65387ad8e8f861f93f961bae5177b5a9b31b5acc324b7","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-12-17T19:45:53Z","title_canon_sha256":"268f43c2566bc0656984ca9369cec41b025d90da6f3aa9a31ee65d0bef43d6e7"},"schema_version":"1.0","source":{"id":"2412.13292","kind":"arxiv","version":2}},"canonical_sha256":"4865dbc180b7ee5812f12549ded7cb4a2a18534fb270e91dc15d9ef0b5914a0f","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"4865dbc180b7ee5812f12549ded7cb4a2a18534fb270e91dc15d9ef0b5914a0f","first_computed_at":"2026-07-05T10:46:59.427703Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:46:59.427703Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"rtZ/wGIWgSnBz15mwc6+6t72N9F1rwEc7kbJRSjl4uts7hN/v8mNLPVgv0aDMqkbJFfUiynbdVAHbvw4aMnYDQ==","signature_status":"signed_v1","signed_at":"2026-07-05T10:46:59.428206Z","signed_message":"canonical_sha256_bytes"},"source_id":"2412.13292","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:3e83519f31f5bf0c893f341d0f7f7ec76d2a756d3d333434da946cf8dba5e5d7","sha256:91dc6981e6c50ab411ad8b6864996867cd3adf76b86c6933d035d5de32df1e88"],"state_sha256":"62cc9ae8e33a135c3d828fed519dd9ad9fbf0d2c5c88938f1514daef887957aa"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"GzNeTN4ZsHfc2aGYYKMq3pt1AOLVSLCnOOkPCRjo/O2GGT+Ltq/tLQRUQyoHjUOLUz3F+EqgfjuGRoFIX1g6Ag==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-13T00:09:23.305179Z","bundle_sha256":"d391d95742754b9e97c131a5c9a71c1a729cd11d291e11d7cfcd9c2d14a82cab"}}