{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:SCABQJXBWJWEI424X6S2ZSTGNZ","short_pith_number":"pith:SCABQJXB","canonical_record":{"source":{"id":"2511.05747","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2025-11-07T22:35:31Z","cross_cats_sorted":[],"title_canon_sha256":"276061df8e0028ec2ddf69b7eacb568040a21437d967eb3291520a80c625a9a7","abstract_canon_sha256":"eb3fb81b79683afd6ab3e4903513b17c2a7efe8753fac18f581cee4a6ca15cfa"},"schema_version":"1.0"},"canonical_sha256":"90801826e1b26c44735cbfa5acca666e73330adcc69de47a78535e9a60f8b7ef","source":{"kind":"arxiv","id":"2511.05747","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2511.05747","created_at":"2026-07-02T01:17:25Z"},{"alias_kind":"arxiv_version","alias_value":"2511.05747v3","created_at":"2026-07-02T01:17:25Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2511.05747","created_at":"2026-07-02T01:17:25Z"},{"alias_kind":"pith_short_12","alias_value":"SCABQJXBWJWE","created_at":"2026-07-02T01:17:25Z"},{"alias_kind":"pith_short_16","alias_value":"SCABQJXBWJWEI424","created_at":"2026-07-02T01:17:25Z"},{"alias_kind":"pith_short_8","alias_value":"SCABQJXB","created_at":"2026-07-02T01:17:25Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:SCABQJXBWJWEI424X6S2ZSTGNZ","target":"record","payload":{"canonical_record":{"source":{"id":"2511.05747","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2025-11-07T22:35:31Z","cross_cats_sorted":[],"title_canon_sha256":"276061df8e0028ec2ddf69b7eacb568040a21437d967eb3291520a80c625a9a7","abstract_canon_sha256":"eb3fb81b79683afd6ab3e4903513b17c2a7efe8753fac18f581cee4a6ca15cfa"},"schema_version":"1.0"},"canonical_sha256":"90801826e1b26c44735cbfa5acca666e73330adcc69de47a78535e9a60f8b7ef","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-02T01:17:25.371322Z","signature_b64":"LTHnZEmfv4A6LT9XjBWZNbrTiWbluwnYcjFrBS3jFuZqKN65FH1Q/PB6PRnztSpst7d9b+W8Wt1XaXfzX5RRBA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"90801826e1b26c44735cbfa5acca666e73330adcc69de47a78535e9a60f8b7ef","last_reissued_at":"2026-07-02T01:17:25.370738Z","signature_status":"signed_v1","first_computed_at":"2026-07-02T01:17:25.370738Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2511.05747","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":"2026-07-02T01:17:25Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"wyCTZfVgXApZ1HJU4e0Z+7oV5h4Z7BhogYpYfxca8vxYI2GT/M3sWgrQur7+jAZi7PLkcaiwWQtswCLra98dBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-01T01:19:25.986487Z"},"content_sha256":"ae757f1eb81aa67ecf36843798243081bdce5f76e4f41a386370010bfe54019c","schema_version":"1.0","event_id":"sha256:ae757f1eb81aa67ecf36843798243081bdce5f76e4f41a386370010bfe54019c"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:SCABQJXBWJWEI424X6S2ZSTGNZ","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"CoT-X: An Adaptive Framework for Cross-Model Chain-of-Thought Transfer and Optimization","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.AI","authors_text":"Benji Peng, Junfeng Hao, Tianyang Wang, Xinyuan Song, Yinzhi Wang, Ziqian Bi","submitted_at":"2025-11-07T22:35:31Z","abstract_excerpt":"Chain-of-Thought (CoT) reasoning enhances the problem-solving ability of large language models (LLMs) but leads to substantial inference overhead, limiting deployment in resource-constrained settings. This paper investigates efficient CoT transfer across models of different scales and architectures through an adaptive reasoning summarization framework. The proposed method compresses reasoning traces via semantic segmentation with importance scoring, budget-aware dynamic compression, and coherence reconstruction, preserving critical reasoning steps while significantly reducing token usage. Expe"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2511.05747","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/2511.05747/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":"2026-07-02T01:17:25Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"MTVb1mZtvTjjNGwqy55nZReFssks97m54LGpkz2R7DmLP27PrJS55Czbjo0nYeg9EmvD9P+jndJA/2eE9FYuAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-01T01:19:25.987074Z"},"content_sha256":"0c9a6d7b8333d3dd80c3ad642b3ef558b3b11f7e82b830f298f321d68d2099b2","schema_version":"1.0","event_id":"sha256:0c9a6d7b8333d3dd80c3ad642b3ef558b3b11f7e82b830f298f321d68d2099b2"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/SCABQJXBWJWEI424X6S2ZSTGNZ/bundle.json","state_url":"https://pith.science/pith/SCABQJXBWJWEI424X6S2ZSTGNZ/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/SCABQJXBWJWEI424X6S2ZSTGNZ/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":"2026-08-01T01:19:25Z","links":{"resolver":"https://pith.science/pith/SCABQJXBWJWEI424X6S2ZSTGNZ","bundle":"https://pith.science/pith/SCABQJXBWJWEI424X6S2ZSTGNZ/bundle.json","state":"https://pith.science/pith/SCABQJXBWJWEI424X6S2ZSTGNZ/state.json","well_known_bundle":"https://pith.science/.well-known/pith/SCABQJXBWJWEI424X6S2ZSTGNZ/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:SCABQJXBWJWEI424X6S2ZSTGNZ","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":"eb3fb81b79683afd6ab3e4903513b17c2a7efe8753fac18f581cee4a6ca15cfa","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2025-11-07T22:35:31Z","title_canon_sha256":"276061df8e0028ec2ddf69b7eacb568040a21437d967eb3291520a80c625a9a7"},"schema_version":"1.0","source":{"id":"2511.05747","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2511.05747","created_at":"2026-07-02T01:17:25Z"},{"alias_kind":"arxiv_version","alias_value":"2511.05747v3","created_at":"2026-07-02T01:17:25Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2511.05747","created_at":"2026-07-02T01:17:25Z"},{"alias_kind":"pith_short_12","alias_value":"SCABQJXBWJWE","created_at":"2026-07-02T01:17:25Z"},{"alias_kind":"pith_short_16","alias_value":"SCABQJXBWJWEI424","created_at":"2026-07-02T01:17:25Z"},{"alias_kind":"pith_short_8","alias_value":"SCABQJXB","created_at":"2026-07-02T01:17:25Z"}],"graph_snapshots":[{"event_id":"sha256:0c9a6d7b8333d3dd80c3ad642b3ef558b3b11f7e82b830f298f321d68d2099b2","target":"graph","created_at":"2026-07-02T01:17:25Z","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/2511.05747/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Chain-of-Thought (CoT) reasoning enhances the problem-solving ability of large language models (LLMs) but leads to substantial inference overhead, limiting deployment in resource-constrained settings. This paper investigates efficient CoT transfer across models of different scales and architectures through an adaptive reasoning summarization framework. The proposed method compresses reasoning traces via semantic segmentation with importance scoring, budget-aware dynamic compression, and coherence reconstruction, preserving critical reasoning steps while significantly reducing token usage. Expe","authors_text":"Benji Peng, Junfeng Hao, Tianyang Wang, Xinyuan Song, Yinzhi Wang, Ziqian Bi","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2025-11-07T22:35:31Z","title":"CoT-X: An Adaptive Framework for Cross-Model Chain-of-Thought Transfer and Optimization"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2511.05747","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:ae757f1eb81aa67ecf36843798243081bdce5f76e4f41a386370010bfe54019c","target":"record","created_at":"2026-07-02T01:17:25Z","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":"eb3fb81b79683afd6ab3e4903513b17c2a7efe8753fac18f581cee4a6ca15cfa","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AI","submitted_at":"2025-11-07T22:35:31Z","title_canon_sha256":"276061df8e0028ec2ddf69b7eacb568040a21437d967eb3291520a80c625a9a7"},"schema_version":"1.0","source":{"id":"2511.05747","kind":"arxiv","version":3}},"canonical_sha256":"90801826e1b26c44735cbfa5acca666e73330adcc69de47a78535e9a60f8b7ef","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"90801826e1b26c44735cbfa5acca666e73330adcc69de47a78535e9a60f8b7ef","first_computed_at":"2026-07-02T01:17:25.370738Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-02T01:17:25.370738Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"LTHnZEmfv4A6LT9XjBWZNbrTiWbluwnYcjFrBS3jFuZqKN65FH1Q/PB6PRnztSpst7d9b+W8Wt1XaXfzX5RRBA==","signature_status":"signed_v1","signed_at":"2026-07-02T01:17:25.371322Z","signed_message":"canonical_sha256_bytes"},"source_id":"2511.05747","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:ae757f1eb81aa67ecf36843798243081bdce5f76e4f41a386370010bfe54019c","sha256:0c9a6d7b8333d3dd80c3ad642b3ef558b3b11f7e82b830f298f321d68d2099b2"],"state_sha256":"d916e868598e90f83a4c4ca47e9bfabca3091c92303e3a1b2ea6b70e64d2413b"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"UgQWSsoVsginMP9kiRgbYzBdtYSDQ4M2yDfSs8wXIg30c+qwraUX+Pw+RaV/SHcTQLZU/xQSedrDio/iTsylDw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-01T01:19:25.991080Z","bundle_sha256":"574fffbbc4bf52a2576c0305dc59a522ea78f226d4a93f5b3925fc5afb1a1051"}}