{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:3FLG2XST2FE4HW5Q5VI2PTSKJW","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":"449a9a1f99c053bb062715820b1bf92c5a5de85288b132eef72611ce8fc4c579","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2025-04-13T16:26:56Z","title_canon_sha256":"67163df0b698c9488bc8c6c65e577387e6ae8aceff9f0635f5692b1830f12582"},"schema_version":"1.0","source":{"id":"2504.09639","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2504.09639","created_at":"2026-07-05T10:48:40Z"},{"alias_kind":"arxiv_version","alias_value":"2504.09639v1","created_at":"2026-07-05T10:48:40Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2504.09639","created_at":"2026-07-05T10:48:40Z"},{"alias_kind":"pith_short_12","alias_value":"3FLG2XST2FE4","created_at":"2026-07-05T10:48:40Z"},{"alias_kind":"pith_short_16","alias_value":"3FLG2XST2FE4HW5Q","created_at":"2026-07-05T10:48:40Z"},{"alias_kind":"pith_short_8","alias_value":"3FLG2XST","created_at":"2026-07-05T10:48:40Z"}],"graph_snapshots":[{"event_id":"sha256:53778f52f724093d3caa6d81ad8d63010a6d655e1cb79e6ba76de06f3c992d6b","target":"graph","created_at":"2026-07-05T10:48:40Z","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/2504.09639/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Recent advancements in large language models (LLMs), such as DeepSeek-R1 and OpenAI-o1, have demonstrated the significant effectiveness of test-time scaling, achieving substantial performance gains across various benchmarks. These advanced models utilize deliberate \"thinking\" steps to systematically enhance answer quality. In this paper, we propose leveraging these high-quality outputs generated by reasoning-intensive models to improve less computationally demanding, non-reasoning models. We explore and compare methodologies for utilizing the answers produced by reasoning models to train and i","authors_text":"Han Zhao, Haotian Wang, Shuaiting Chen, Sitong Zhao, Xiangang Li, Xiaoyu Tian, Yiping Peng, Yunjie Ji","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2025-04-13T16:26:56Z","title":"Leveraging Reasoning Model Answers to Enhance Non-Reasoning Model Capability"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2504.09639","kind":"arxiv","version":1},"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:e501c4c6f2b80da147a8f2d4e9796e9cd3891fbf8b01dacac23b0d3178fcc72d","target":"record","created_at":"2026-07-05T10:48:40Z","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":"449a9a1f99c053bb062715820b1bf92c5a5de85288b132eef72611ce8fc4c579","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2025-04-13T16:26:56Z","title_canon_sha256":"67163df0b698c9488bc8c6c65e577387e6ae8aceff9f0635f5692b1830f12582"},"schema_version":"1.0","source":{"id":"2504.09639","kind":"arxiv","version":1}},"canonical_sha256":"d9566d5e53d149c3dbb0ed51a7ce4a4dba1e978e367eba838d72e43820e6b9ac","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"d9566d5e53d149c3dbb0ed51a7ce4a4dba1e978e367eba838d72e43820e6b9ac","first_computed_at":"2026-07-05T10:48:40.537932Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:48:40.537932Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"aPQHmeFEd3TP53XYEvAIFD8UC8Wsatsu1TLbN57/nQz7X1GQ9TTbCtISIyJXbvnftmorALorySg0MxQ/ca70Bg==","signature_status":"signed_v1","signed_at":"2026-07-05T10:48:40.538518Z","signed_message":"canonical_sha256_bytes"},"source_id":"2504.09639","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:e501c4c6f2b80da147a8f2d4e9796e9cd3891fbf8b01dacac23b0d3178fcc72d","sha256:53778f52f724093d3caa6d81ad8d63010a6d655e1cb79e6ba76de06f3c992d6b"],"state_sha256":"aa6a41ca31390fb014267405f6b2fd583cd49750b1edc73d2d339082972dcb82"}