{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:QHDATL6PRPHOOQEJOJXIAGEP2R","short_pith_number":"pith:QHDATL6P","canonical_record":{"source":{"id":"2406.03816","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-06-06T07:40:00Z","cross_cats_sorted":[],"title_canon_sha256":"e0193e56630e62ecefc5e26869b0d34823cf01b3f95d8167785825e3404eb6e0","abstract_canon_sha256":"09d139f3b9f099fa0afcab3c9365bb0c8f1a88174f9455665dfd43170a5e94f0"},"schema_version":"1.0"},"canonical_sha256":"81c609afcf8bcee74089726e80188fd45b420521cc68725ab2c7477629df50a1","source":{"kind":"arxiv","id":"2406.03816","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2406.03816","created_at":"2026-07-05T09:36:41Z"},{"alias_kind":"arxiv_version","alias_value":"2406.03816v3","created_at":"2026-07-05T09:36:41Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2406.03816","created_at":"2026-07-05T09:36:41Z"},{"alias_kind":"pith_short_12","alias_value":"QHDATL6PRPHO","created_at":"2026-07-05T09:36:41Z"},{"alias_kind":"pith_short_16","alias_value":"QHDATL6PRPHOOQEJ","created_at":"2026-07-05T09:36:41Z"},{"alias_kind":"pith_short_8","alias_value":"QHDATL6P","created_at":"2026-07-05T09:36:41Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:QHDATL6PRPHOOQEJOJXIAGEP2R","target":"record","payload":{"canonical_record":{"source":{"id":"2406.03816","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-06-06T07:40:00Z","cross_cats_sorted":[],"title_canon_sha256":"e0193e56630e62ecefc5e26869b0d34823cf01b3f95d8167785825e3404eb6e0","abstract_canon_sha256":"09d139f3b9f099fa0afcab3c9365bb0c8f1a88174f9455665dfd43170a5e94f0"},"schema_version":"1.0"},"canonical_sha256":"81c609afcf8bcee74089726e80188fd45b420521cc68725ab2c7477629df50a1","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:36:41.361910Z","signature_b64":"O0eabWi+CZi5Z+yZEH3a+TnpbWhRwZx+/VOg9MJ9z/FlboD6Om29ST/+9kvLdKdseqKUx+AiNmNTtnMEPFPcDg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"81c609afcf8bcee74089726e80188fd45b420521cc68725ab2c7477629df50a1","last_reissued_at":"2026-07-05T09:36:41.361420Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:36:41.361420Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2406.03816","source_version":3,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T09:36:41Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"MbxUV8daRTFDGuvh3OV8YrxSpy2O6XQ+C/D6/h+5pelUasAZB539kFGWpBiBP7roLgCz5nN8v7X2sNY0/seuCA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T23:29:36.157619Z"},"content_sha256":"5a77bcba4fe6f56b09aa5130874a5c854e4ee16a89b27934dad3696087c364a2","schema_version":"1.0","event_id":"sha256:5a77bcba4fe6f56b09aa5130874a5c854e4ee16a89b27934dad3696087c364a2"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:QHDATL6PRPHOOQEJOJXIAGEP2R","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"ReST-MCTS*: LLM Self-Training via Process Reward Guided Tree Search","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Dan Zhang, Jie Tang, Sining Zhoubian, Yisong Yue, Yuxiao Dong, Ziniu Hu","submitted_at":"2024-06-06T07:40:00Z","abstract_excerpt":"Recent methodologies in LLM self-training mostly rely on LLM generating responses and filtering those with correct output answers as training data. This approach often yields a low-quality fine-tuning training set (e.g., incorrect plans or intermediate reasoning). In this paper, we develop a reinforced self-training approach, called ReST-MCTS*, based on integrating process reward guidance with tree search MCTS* for collecting higher-quality reasoning traces as well as per-step value to train policy and reward models. ReST-MCTS* circumvents the per-step manual annotation typically used to train"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2406.03816","kind":"arxiv","version":3},"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/2406.03816/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":"2026-07-05T09:36:41Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"xUI8mkfVZZgsxUxj3OkUnF030biqZFvMPuMny13UrQD2PXuQcAA3sV/lVPFj9lxr3lqMg2o4k5CWkbLKOm43BQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T23:29:36.158586Z"},"content_sha256":"bd8bbeddaeb4b226f1f5191e558f4c9ae712a60f6d684c22b79c00f2aa2bac4e","schema_version":"1.0","event_id":"sha256:bd8bbeddaeb4b226f1f5191e558f4c9ae712a60f6d684c22b79c00f2aa2bac4e"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/QHDATL6PRPHOOQEJOJXIAGEP2R/bundle.json","state_url":"https://pith.science/pith/QHDATL6PRPHOOQEJOJXIAGEP2R/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/QHDATL6PRPHOOQEJOJXIAGEP2R/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":"2026-08-04T23:29:36Z","links":{"resolver":"https://pith.science/pith/QHDATL6PRPHOOQEJOJXIAGEP2R","bundle":"https://pith.science/pith/QHDATL6PRPHOOQEJOJXIAGEP2R/bundle.json","state":"https://pith.science/pith/QHDATL6PRPHOOQEJOJXIAGEP2R/state.json","well_known_bundle":"https://pith.science/.well-known/pith/QHDATL6PRPHOOQEJOJXIAGEP2R/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:QHDATL6PRPHOOQEJOJXIAGEP2R","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":"09d139f3b9f099fa0afcab3c9365bb0c8f1a88174f9455665dfd43170a5e94f0","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-06-06T07:40:00Z","title_canon_sha256":"e0193e56630e62ecefc5e26869b0d34823cf01b3f95d8167785825e3404eb6e0"},"schema_version":"1.0","source":{"id":"2406.03816","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2406.03816","created_at":"2026-07-05T09:36:41Z"},{"alias_kind":"arxiv_version","alias_value":"2406.03816v3","created_at":"2026-07-05T09:36:41Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2406.03816","created_at":"2026-07-05T09:36:41Z"},{"alias_kind":"pith_short_12","alias_value":"QHDATL6PRPHO","created_at":"2026-07-05T09:36:41Z"},{"alias_kind":"pith_short_16","alias_value":"QHDATL6PRPHOOQEJ","created_at":"2026-07-05T09:36:41Z"},{"alias_kind":"pith_short_8","alias_value":"QHDATL6P","created_at":"2026-07-05T09:36:41Z"}],"graph_snapshots":[{"event_id":"sha256:bd8bbeddaeb4b226f1f5191e558f4c9ae712a60f6d684c22b79c00f2aa2bac4e","target":"graph","created_at":"2026-07-05T09:36:41Z","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/2406.03816/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Recent methodologies in LLM self-training mostly rely on LLM generating responses and filtering those with correct output answers as training data. This approach often yields a low-quality fine-tuning training set (e.g., incorrect plans or intermediate reasoning). In this paper, we develop a reinforced self-training approach, called ReST-MCTS*, based on integrating process reward guidance with tree search MCTS* for collecting higher-quality reasoning traces as well as per-step value to train policy and reward models. ReST-MCTS* circumvents the per-step manual annotation typically used to train","authors_text":"Dan Zhang, Jie Tang, Sining Zhoubian, Yisong Yue, Yuxiao Dong, Ziniu Hu","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-06-06T07:40:00Z","title":"ReST-MCTS*: LLM Self-Training via Process Reward Guided Tree Search"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2406.03816","kind":"arxiv","version":3},"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":"sha256:5a77bcba4fe6f56b09aa5130874a5c854e4ee16a89b27934dad3696087c364a2","target":"record","created_at":"2026-07-05T09:36:41Z","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":"09d139f3b9f099fa0afcab3c9365bb0c8f1a88174f9455665dfd43170a5e94f0","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-06-06T07:40:00Z","title_canon_sha256":"e0193e56630e62ecefc5e26869b0d34823cf01b3f95d8167785825e3404eb6e0"},"schema_version":"1.0","source":{"id":"2406.03816","kind":"arxiv","version":3}},"canonical_sha256":"81c609afcf8bcee74089726e80188fd45b420521cc68725ab2c7477629df50a1","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"81c609afcf8bcee74089726e80188fd45b420521cc68725ab2c7477629df50a1","first_computed_at":"2026-07-05T09:36:41.361420Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:36:41.361420Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"O0eabWi+CZi5Z+yZEH3a+TnpbWhRwZx+/VOg9MJ9z/FlboD6Om29ST/+9kvLdKdseqKUx+AiNmNTtnMEPFPcDg==","signature_status":"signed_v1","signed_at":"2026-07-05T09:36:41.361910Z","signed_message":"canonical_sha256_bytes"},"source_id":"2406.03816","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:5a77bcba4fe6f56b09aa5130874a5c854e4ee16a89b27934dad3696087c364a2","sha256:bd8bbeddaeb4b226f1f5191e558f4c9ae712a60f6d684c22b79c00f2aa2bac4e"],"state_sha256":"ef6c4d839230e84c2778621af1e9cea36cf450371c3b29c19a74e02dd5ab1a38"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"x5wN/p4+oV57bi5aQoXWNhRhUmsRktB93W6fsYH50FAwKqoKjVDHLb8jAQO5uEb8CoT3+00nTasscLU5+MkLDQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-04T23:29:36.165465Z","bundle_sha256":"631f402b867047451a59ef7317d11237c2d69e98b0330fa8a64b543a28840a01"}}