{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:DPZRGMWVP6SOU5MYXUIU7ES7SO","short_pith_number":"pith:DPZRGMWV","canonical_record":{"source":{"id":"2410.16033","kind":"arxiv","version":4},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-10-18T04:38:21Z","cross_cats_sorted":["cs.AI","cs.LG"],"title_canon_sha256":"2c95b4efbb8465c16cf53234b1db95bd2835f77539ac85aaaca2000a8c6eb965","abstract_canon_sha256":"14bd791812f31d0431ef4ea7f2abf9e52bdb90af4f3c7aa91f1d5a70091cfa5e"},"schema_version":"1.0"},"canonical_sha256":"1bf31332d57fa4ea7598bd114f925f93908dbe93e76a579a950ae8a61b8efcd6","source":{"kind":"arxiv","id":"2410.16033","version":4},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2410.16033","created_at":"2026-07-05T12:03:43Z"},{"alias_kind":"arxiv_version","alias_value":"2410.16033v4","created_at":"2026-07-05T12:03:43Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2410.16033","created_at":"2026-07-05T12:03:43Z"},{"alias_kind":"pith_short_12","alias_value":"DPZRGMWVP6SO","created_at":"2026-07-05T12:03:43Z"},{"alias_kind":"pith_short_16","alias_value":"DPZRGMWVP6SOU5MY","created_at":"2026-07-05T12:03:43Z"},{"alias_kind":"pith_short_8","alias_value":"DPZRGMWV","created_at":"2026-07-05T12:03:43Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:DPZRGMWVP6SOU5MYXUIU7ES7SO","target":"record","payload":{"canonical_record":{"source":{"id":"2410.16033","kind":"arxiv","version":4},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-10-18T04:38:21Z","cross_cats_sorted":["cs.AI","cs.LG"],"title_canon_sha256":"2c95b4efbb8465c16cf53234b1db95bd2835f77539ac85aaaca2000a8c6eb965","abstract_canon_sha256":"14bd791812f31d0431ef4ea7f2abf9e52bdb90af4f3c7aa91f1d5a70091cfa5e"},"schema_version":"1.0"},"canonical_sha256":"1bf31332d57fa4ea7598bd114f925f93908dbe93e76a579a950ae8a61b8efcd6","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T12:03:43.739229Z","signature_b64":"FRwDkzeePkk0Dv2IIzIMYmmzJ6p/w1ZtJE+zmoTxrK6ylzY9tyjYBxRmcyRrY260paDnljd2sHpLH2a3hxRRAw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"1bf31332d57fa4ea7598bd114f925f93908dbe93e76a579a950ae8a61b8efcd6","last_reissued_at":"2026-07-05T12:03:43.738706Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T12:03:43.738706Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2410.16033","source_version":4,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T12:03:43Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"CytyHxuY0UZtCeGJR5KBeSD3TtbtTkc21PpLV6E5Arcyw13cXct7G9eG7e2r14dbR1f+yvmwFW4eh0+vT/HWBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-09T02:19:13.788580Z"},"content_sha256":"b485a5a7937b3f82ec1070c3a0649820ce07ec714846073b5fceec464c1581ab","schema_version":"1.0","event_id":"sha256:b485a5a7937b3f82ec1070c3a0649820ce07ec714846073b5fceec464c1581ab"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:DPZRGMWVP6SOU5MYXUIU7ES7SO","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"TreeBoN: Enhancing Inference-Time Alignment with Speculative Tree-Search and Best-of-N Sampling","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI","cs.LG"],"primary_cat":"cs.CL","authors_text":"Chenhao Zhu, Huazheng Wang, Jiacheng Guo, Jiahao Qiu, Jiayi Geng, Kaixuan Huang, Ling Yang, Mengdi Wang, Xinzhe Juan, Yifan Zeng, Yifu Lu, Yue Wu","submitted_at":"2024-10-18T04:38:21Z","abstract_excerpt":"Inference-time alignment enhances the performance of large language models without requiring additional training or fine-tuning but presents challenges due to balancing computational efficiency with high-quality output. Best-of-N (BoN) sampling, as a simple yet powerful approach, generates multiple responses and selects the best one, achieving improved performance but with a high computational cost. We propose TreeBoN, a novel framework that integrates a speculative tree-search strategy into Best-of-N (BoN) Sampling. TreeBoN maintains a set of parent nodes, iteratively branching and pruning lo"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2410.16033","kind":"arxiv","version":4},"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/2410.16033/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":"2026-07-05T12:03:43Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"PntQJNbAKaw08Afu/pY/y5uJUId74HGybpYOMflYJWayDbM8+wzx8ZekugNVHEBZH7dIb0RF0KSQL4Cm1QLlCw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-09T02:19:13.788964Z"},"content_sha256":"655def9f068fcda3407cfbbf9971a134e772fd59ad5204e26c1b416d6fd31bb6","schema_version":"1.0","event_id":"sha256:655def9f068fcda3407cfbbf9971a134e772fd59ad5204e26c1b416d6fd31bb6"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/DPZRGMWVP6SOU5MYXUIU7ES7SO/bundle.json","state_url":"https://pith.science/pith/DPZRGMWVP6SOU5MYXUIU7ES7SO/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/DPZRGMWVP6SOU5MYXUIU7ES7SO/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":"2026-07-09T02:19:13Z","links":{"resolver":"https://pith.science/pith/DPZRGMWVP6SOU5MYXUIU7ES7SO","bundle":"https://pith.science/pith/DPZRGMWVP6SOU5MYXUIU7ES7SO/bundle.json","state":"https://pith.science/pith/DPZRGMWVP6SOU5MYXUIU7ES7SO/state.json","well_known_bundle":"https://pith.science/.well-known/pith/DPZRGMWVP6SOU5MYXUIU7ES7SO/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:DPZRGMWVP6SOU5MYXUIU7ES7SO","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":"14bd791812f31d0431ef4ea7f2abf9e52bdb90af4f3c7aa91f1d5a70091cfa5e","cross_cats_sorted":["cs.AI","cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-10-18T04:38:21Z","title_canon_sha256":"2c95b4efbb8465c16cf53234b1db95bd2835f77539ac85aaaca2000a8c6eb965"},"schema_version":"1.0","source":{"id":"2410.16033","kind":"arxiv","version":4}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2410.16033","created_at":"2026-07-05T12:03:43Z"},{"alias_kind":"arxiv_version","alias_value":"2410.16033v4","created_at":"2026-07-05T12:03:43Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2410.16033","created_at":"2026-07-05T12:03:43Z"},{"alias_kind":"pith_short_12","alias_value":"DPZRGMWVP6SO","created_at":"2026-07-05T12:03:43Z"},{"alias_kind":"pith_short_16","alias_value":"DPZRGMWVP6SOU5MY","created_at":"2026-07-05T12:03:43Z"},{"alias_kind":"pith_short_8","alias_value":"DPZRGMWV","created_at":"2026-07-05T12:03:43Z"}],"graph_snapshots":[{"event_id":"sha256:655def9f068fcda3407cfbbf9971a134e772fd59ad5204e26c1b416d6fd31bb6","target":"graph","created_at":"2026-07-05T12:03:43Z","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/2410.16033/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Inference-time alignment enhances the performance of large language models without requiring additional training or fine-tuning but presents challenges due to balancing computational efficiency with high-quality output. Best-of-N (BoN) sampling, as a simple yet powerful approach, generates multiple responses and selects the best one, achieving improved performance but with a high computational cost. We propose TreeBoN, a novel framework that integrates a speculative tree-search strategy into Best-of-N (BoN) Sampling. TreeBoN maintains a set of parent nodes, iteratively branching and pruning lo","authors_text":"Chenhao Zhu, Huazheng Wang, Jiacheng Guo, Jiahao Qiu, Jiayi Geng, Kaixuan Huang, Ling Yang, Mengdi Wang, Xinzhe Juan, Yifan Zeng, Yifu Lu, Yue Wu","cross_cats":["cs.AI","cs.LG"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-10-18T04:38:21Z","title":"TreeBoN: Enhancing Inference-Time Alignment with Speculative Tree-Search and Best-of-N Sampling"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2410.16033","kind":"arxiv","version":4},"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:b485a5a7937b3f82ec1070c3a0649820ce07ec714846073b5fceec464c1581ab","target":"record","created_at":"2026-07-05T12:03:43Z","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":"14bd791812f31d0431ef4ea7f2abf9e52bdb90af4f3c7aa91f1d5a70091cfa5e","cross_cats_sorted":["cs.AI","cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-10-18T04:38:21Z","title_canon_sha256":"2c95b4efbb8465c16cf53234b1db95bd2835f77539ac85aaaca2000a8c6eb965"},"schema_version":"1.0","source":{"id":"2410.16033","kind":"arxiv","version":4}},"canonical_sha256":"1bf31332d57fa4ea7598bd114f925f93908dbe93e76a579a950ae8a61b8efcd6","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"1bf31332d57fa4ea7598bd114f925f93908dbe93e76a579a950ae8a61b8efcd6","first_computed_at":"2026-07-05T12:03:43.738706Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T12:03:43.738706Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"FRwDkzeePkk0Dv2IIzIMYmmzJ6p/w1ZtJE+zmoTxrK6ylzY9tyjYBxRmcyRrY260paDnljd2sHpLH2a3hxRRAw==","signature_status":"signed_v1","signed_at":"2026-07-05T12:03:43.739229Z","signed_message":"canonical_sha256_bytes"},"source_id":"2410.16033","source_kind":"arxiv","source_version":4}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:b485a5a7937b3f82ec1070c3a0649820ce07ec714846073b5fceec464c1581ab","sha256:655def9f068fcda3407cfbbf9971a134e772fd59ad5204e26c1b416d6fd31bb6"],"state_sha256":"72784654f1741c9bda7ed70aeeb5971b8c8a6ec0b6b34922b476c221812ccf8d"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"qs960WyC+7LT6nVzvzY/qD7KqqTqVU9gxJ3MKSA9k2vcbeT2KaTf8N/LPJlEiiEl6jGKwOQrEmTdhjq65T/1Ag==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-09T02:19:13.791022Z","bundle_sha256":"82959aaebbcab01692bc85229ab8982a0cd40aca4a05ed1f9c96f6ce38b8f03d"}}