{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:NGEB7FQLCJELYHBEDVGBIKHL6S","short_pith_number":"pith:NGEB7FQL","canonical_record":{"source":{"id":"2410.01044","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2024-10-01T20:05:51Z","cross_cats_sorted":["cs.CL"],"title_canon_sha256":"43a563f1fd65299d5d2009f6d671f61a2a988c54a08614f98d03df7a4ac6b3d1","abstract_canon_sha256":"d6afea56e3d60e209fa54693d0a8a417a09f92967a9273a5fcd5fd6ed9b20be8"},"schema_version":"1.0"},"canonical_sha256":"69881f960b1248bc1c241d4c1428ebf48812d2790a8fb3590846046355a048f3","source":{"kind":"arxiv","id":"2410.01044","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2410.01044","created_at":"2026-07-05T11:21:36Z"},{"alias_kind":"arxiv_version","alias_value":"2410.01044v2","created_at":"2026-07-05T11:21:36Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2410.01044","created_at":"2026-07-05T11:21:36Z"},{"alias_kind":"pith_short_12","alias_value":"NGEB7FQLCJEL","created_at":"2026-07-05T11:21:36Z"},{"alias_kind":"pith_short_16","alias_value":"NGEB7FQLCJELYHBE","created_at":"2026-07-05T11:21:36Z"},{"alias_kind":"pith_short_8","alias_value":"NGEB7FQL","created_at":"2026-07-05T11:21:36Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:NGEB7FQLCJELYHBEDVGBIKHL6S","target":"record","payload":{"canonical_record":{"source":{"id":"2410.01044","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2024-10-01T20:05:51Z","cross_cats_sorted":["cs.CL"],"title_canon_sha256":"43a563f1fd65299d5d2009f6d671f61a2a988c54a08614f98d03df7a4ac6b3d1","abstract_canon_sha256":"d6afea56e3d60e209fa54693d0a8a417a09f92967a9273a5fcd5fd6ed9b20be8"},"schema_version":"1.0"},"canonical_sha256":"69881f960b1248bc1c241d4c1428ebf48812d2790a8fb3590846046355a048f3","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:21:36.303874Z","signature_b64":"oywOgpsG0Tepi66W9ofTtQuFOieBx3HcBUZpWl6Nvs+mXA7vxWbkqzml0WsWTrh2p3UeaVETqQIBNz3IseTaDg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"69881f960b1248bc1c241d4c1428ebf48812d2790a8fb3590846046355a048f3","last_reissued_at":"2026-07-05T11:21:36.303356Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:21:36.303356Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2410.01044","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":"2026-07-05T11:21:36Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"wA28V0pEW5xBXa+c2E4PROyhqTKw1CFnJOTT/vNn+aeo2EBWtU53eLlkwkBMbjFMGR7AGX+QmZUsr7XB7zuaAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-16T09:57:28.125557Z"},"content_sha256":"1725e0ce7b0e0ff303f004bb378fafa788176e8648b1789c2798aecd2f0d23f0","schema_version":"1.0","event_id":"sha256:1725e0ce7b0e0ff303f004bb378fafa788176e8648b1789c2798aecd2f0d23f0"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:NGEB7FQLCJELYHBEDVGBIKHL6S","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"RATIONALYST: Mining Implicit Rationales for Process Supervision of Reasoning","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.CL"],"primary_cat":"cs.AI","authors_text":"Andrew Wang, Benjamin Van Durme, Chuyu Liu, Daniel Khashabi, Dongwei Jiang, Guoxuan Wang, Jingyu Zhang, Yining Lu","submitted_at":"2024-10-01T20:05:51Z","abstract_excerpt":"The reasoning steps generated by LLMs might be incomplete, as they mimic logical leaps common in everyday communication found in their pre-training data: underlying rationales are frequently left implicit (unstated). To address this challenge, we introduce RATIONALYST, a model for process-supervision of reasoning based on pre-training on a vast collection of rationale annotations extracted from unlabeled data. We extract 79k rationales from web-scale unlabelled dataset (the Pile) and a combination of reasoning datasets with minimal human intervention. This web-scale pre-training for reasoning "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2410.01044","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/2410.01044/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":"2026-07-05T11:21:36Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"QSQbo59JOZy5erWgb8moMillVrtn3waUYNpOp7klF9gZk4XnQH/IQXiQJgyfXloJzL0C4GzgVNCzZs1vj0wYAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-16T09:57:28.125953Z"},"content_sha256":"b46e11acdd363d52282a8fe34f88bb73e04b8c0b8ccdae91b5826a81a0d0c57d","schema_version":"1.0","event_id":"sha256:b46e11acdd363d52282a8fe34f88bb73e04b8c0b8ccdae91b5826a81a0d0c57d"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/NGEB7FQLCJELYHBEDVGBIKHL6S/bundle.json","state_url":"https://pith.science/pith/NGEB7FQLCJELYHBEDVGBIKHL6S/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/NGEB7FQLCJELYHBEDVGBIKHL6S/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":"2026-07-16T09:57:28Z","links":{"resolver":"https://pith.science/pith/NGEB7FQLCJELYHBEDVGBIKHL6S","bundle":"https://pith.science/pith/NGEB7FQLCJELYHBEDVGBIKHL6S/bundle.json","state":"https://pith.science/pith/NGEB7FQLCJELYHBEDVGBIKHL6S/state.json","well_known_bundle":"https://pith.science/.well-known/pith/NGEB7FQLCJELYHBEDVGBIKHL6S/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:NGEB7FQLCJELYHBEDVGBIKHL6S","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":"d6afea56e3d60e209fa54693d0a8a417a09f92967a9273a5fcd5fd6ed9b20be8","cross_cats_sorted":["cs.CL"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2024-10-01T20:05:51Z","title_canon_sha256":"43a563f1fd65299d5d2009f6d671f61a2a988c54a08614f98d03df7a4ac6b3d1"},"schema_version":"1.0","source":{"id":"2410.01044","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2410.01044","created_at":"2026-07-05T11:21:36Z"},{"alias_kind":"arxiv_version","alias_value":"2410.01044v2","created_at":"2026-07-05T11:21:36Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2410.01044","created_at":"2026-07-05T11:21:36Z"},{"alias_kind":"pith_short_12","alias_value":"NGEB7FQLCJEL","created_at":"2026-07-05T11:21:36Z"},{"alias_kind":"pith_short_16","alias_value":"NGEB7FQLCJELYHBE","created_at":"2026-07-05T11:21:36Z"},{"alias_kind":"pith_short_8","alias_value":"NGEB7FQL","created_at":"2026-07-05T11:21:36Z"}],"graph_snapshots":[{"event_id":"sha256:b46e11acdd363d52282a8fe34f88bb73e04b8c0b8ccdae91b5826a81a0d0c57d","target":"graph","created_at":"2026-07-05T11:21:36Z","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/2410.01044/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"The reasoning steps generated by LLMs might be incomplete, as they mimic logical leaps common in everyday communication found in their pre-training data: underlying rationales are frequently left implicit (unstated). To address this challenge, we introduce RATIONALYST, a model for process-supervision of reasoning based on pre-training on a vast collection of rationale annotations extracted from unlabeled data. We extract 79k rationales from web-scale unlabelled dataset (the Pile) and a combination of reasoning datasets with minimal human intervention. This web-scale pre-training for reasoning ","authors_text":"Andrew Wang, Benjamin Van Durme, Chuyu Liu, Daniel Khashabi, Dongwei Jiang, Guoxuan Wang, Jingyu Zhang, Yining Lu","cross_cats":["cs.CL"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2024-10-01T20:05:51Z","title":"RATIONALYST: Mining Implicit Rationales for Process Supervision of Reasoning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2410.01044","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":"sha256:1725e0ce7b0e0ff303f004bb378fafa788176e8648b1789c2798aecd2f0d23f0","target":"record","created_at":"2026-07-05T11:21:36Z","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":"d6afea56e3d60e209fa54693d0a8a417a09f92967a9273a5fcd5fd6ed9b20be8","cross_cats_sorted":["cs.CL"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2024-10-01T20:05:51Z","title_canon_sha256":"43a563f1fd65299d5d2009f6d671f61a2a988c54a08614f98d03df7a4ac6b3d1"},"schema_version":"1.0","source":{"id":"2410.01044","kind":"arxiv","version":2}},"canonical_sha256":"69881f960b1248bc1c241d4c1428ebf48812d2790a8fb3590846046355a048f3","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"69881f960b1248bc1c241d4c1428ebf48812d2790a8fb3590846046355a048f3","first_computed_at":"2026-07-05T11:21:36.303356Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:21:36.303356Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"oywOgpsG0Tepi66W9ofTtQuFOieBx3HcBUZpWl6Nvs+mXA7vxWbkqzml0WsWTrh2p3UeaVETqQIBNz3IseTaDg==","signature_status":"signed_v1","signed_at":"2026-07-05T11:21:36.303874Z","signed_message":"canonical_sha256_bytes"},"source_id":"2410.01044","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:1725e0ce7b0e0ff303f004bb378fafa788176e8648b1789c2798aecd2f0d23f0","sha256:b46e11acdd363d52282a8fe34f88bb73e04b8c0b8ccdae91b5826a81a0d0c57d"],"state_sha256":"5b9a3abdc994fb3539dc7e60f2c7a2b6371e935ebc55ddadb4efabece8937ae7"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"nxje8YIGXQ4uwv2ldrpVnHH1woQU56Y63mBhwaXIPMDhdTx8Dpbqu7Wkd8KCwQWS0SyXZqD8gg4KbBjf/HDBDw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-16T09:57:28.128264Z","bundle_sha256":"27d4c138947c12ffa90783f661fd0933a8804e068c14d1587151dd79827840bf"}}