{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:QNBH2RNTHW3MBTSDVYSUJSVHJM","short_pith_number":"pith:QNBH2RNT","canonical_record":{"source":{"id":"2505.20700","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2025-05-27T04:08:11Z","cross_cats_sorted":[],"title_canon_sha256":"6668252c4af9d652488f4daebcaf56f976ddcf3808c30d8da3cdc403a324d71e","abstract_canon_sha256":"e24db3450d2c709b320f491f63357c87ac67e76a89360d156191c4f27f7509c8"},"schema_version":"1.0"},"canonical_sha256":"83427d45b33db6c0ce43ae2544caa74b1fd20f5e019b36d1f6e03afa9b6b7f9c","source":{"kind":"arxiv","id":"2505.20700","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2505.20700","created_at":"2026-07-05T11:10:17Z"},{"alias_kind":"arxiv_version","alias_value":"2505.20700v1","created_at":"2026-07-05T11:10:17Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2505.20700","created_at":"2026-07-05T11:10:17Z"},{"alias_kind":"pith_short_12","alias_value":"QNBH2RNTHW3M","created_at":"2026-07-05T11:10:17Z"},{"alias_kind":"pith_short_16","alias_value":"QNBH2RNTHW3MBTSD","created_at":"2026-07-05T11:10:17Z"},{"alias_kind":"pith_short_8","alias_value":"QNBH2RNT","created_at":"2026-07-05T11:10:17Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:QNBH2RNTHW3MBTSDVYSUJSVHJM","target":"record","payload":{"canonical_record":{"source":{"id":"2505.20700","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2025-05-27T04:08:11Z","cross_cats_sorted":[],"title_canon_sha256":"6668252c4af9d652488f4daebcaf56f976ddcf3808c30d8da3cdc403a324d71e","abstract_canon_sha256":"e24db3450d2c709b320f491f63357c87ac67e76a89360d156191c4f27f7509c8"},"schema_version":"1.0"},"canonical_sha256":"83427d45b33db6c0ce43ae2544caa74b1fd20f5e019b36d1f6e03afa9b6b7f9c","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:10:17.137209Z","signature_b64":"/JbTHnOxGFpYWoKICWpSepPO4Ys/yZkCO5sluBHt3Wv0dhhyEhb4VJJC46pyN5m5WSpd/DKnyUyW8pIDD0sDBw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"83427d45b33db6c0ce43ae2544caa74b1fd20f5e019b36d1f6e03afa9b6b7f9c","last_reissued_at":"2026-07-05T11:10:17.136721Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:10:17.136721Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2505.20700","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T11:10:17Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Vz1U3kqt/fkaHNrAbAyckqHO1yhOuyJVPARlv6aDnu3bb/ne/FIQxKfNYoWJDjAtf9uf4PxRrX2l7d5OEHOkCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-08T06:44:06.392496Z"},"content_sha256":"688f085b33ae5043e7e00aab2471aec68f88009f1d2d24139051dfe22acd61fa","schema_version":"1.0","event_id":"sha256:688f085b33ae5043e7e00aab2471aec68f88009f1d2d24139051dfe22acd61fa"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:QNBH2RNTHW3MBTSDVYSUJSVHJM","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Beyond Templates: Dynamic Adaptation of Reasoning Demonstrations via Feasibility-Aware Exploration","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Binbin Lin, Chen Binhui, Ke Li, Ping Li, Weihang Pan, Yong Wu","submitted_at":"2025-05-27T04:08:11Z","abstract_excerpt":"Large language models (LLMs) have shown remarkable reasoning capabilities, yet aligning such abilities to small language models (SLMs) remains a challenge due to distributional mismatches and limited model capacity. Existing reasoning datasets, typically designed for powerful LLMs, often lead to degraded performance when directly applied to weaker models. In this work, we introduce Dynamic Adaptation of Reasoning Trajectories (DART), a novel data adaptation framework that bridges the capability gap between expert reasoning trajectories and diverse SLMs. Instead of uniformly imitating expert st"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2505.20700","kind":"arxiv","version":1},"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/2505.20700/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":"2026-07-05T11:10:17Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"XMyItBJvq6CJk/GfLncLjMGdbfTY0Gtqnmh+zRwVFzgueTe56c8ijartr0rEZIm2Zi6gYOHw0qTlU0tXc2NoCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-08T06:44:06.393419Z"},"content_sha256":"95c2e33ded569fe82a8b5b63a587f1b2fe479ed985c89d32953424f2f9805347","schema_version":"1.0","event_id":"sha256:95c2e33ded569fe82a8b5b63a587f1b2fe479ed985c89d32953424f2f9805347"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/QNBH2RNTHW3MBTSDVYSUJSVHJM/bundle.json","state_url":"https://pith.science/pith/QNBH2RNTHW3MBTSDVYSUJSVHJM/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/QNBH2RNTHW3MBTSDVYSUJSVHJM/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":"2026-08-08T06:44:06Z","links":{"resolver":"https://pith.science/pith/QNBH2RNTHW3MBTSDVYSUJSVHJM","bundle":"https://pith.science/pith/QNBH2RNTHW3MBTSDVYSUJSVHJM/bundle.json","state":"https://pith.science/pith/QNBH2RNTHW3MBTSDVYSUJSVHJM/state.json","well_known_bundle":"https://pith.science/.well-known/pith/QNBH2RNTHW3MBTSDVYSUJSVHJM/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:QNBH2RNTHW3MBTSDVYSUJSVHJM","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":"e24db3450d2c709b320f491f63357c87ac67e76a89360d156191c4f27f7509c8","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2025-05-27T04:08:11Z","title_canon_sha256":"6668252c4af9d652488f4daebcaf56f976ddcf3808c30d8da3cdc403a324d71e"},"schema_version":"1.0","source":{"id":"2505.20700","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2505.20700","created_at":"2026-07-05T11:10:17Z"},{"alias_kind":"arxiv_version","alias_value":"2505.20700v1","created_at":"2026-07-05T11:10:17Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2505.20700","created_at":"2026-07-05T11:10:17Z"},{"alias_kind":"pith_short_12","alias_value":"QNBH2RNTHW3M","created_at":"2026-07-05T11:10:17Z"},{"alias_kind":"pith_short_16","alias_value":"QNBH2RNTHW3MBTSD","created_at":"2026-07-05T11:10:17Z"},{"alias_kind":"pith_short_8","alias_value":"QNBH2RNT","created_at":"2026-07-05T11:10:17Z"}],"graph_snapshots":[{"event_id":"sha256:95c2e33ded569fe82a8b5b63a587f1b2fe479ed985c89d32953424f2f9805347","target":"graph","created_at":"2026-07-05T11:10:17Z","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/2505.20700/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Large language models (LLMs) have shown remarkable reasoning capabilities, yet aligning such abilities to small language models (SLMs) remains a challenge due to distributional mismatches and limited model capacity. Existing reasoning datasets, typically designed for powerful LLMs, often lead to degraded performance when directly applied to weaker models. In this work, we introduce Dynamic Adaptation of Reasoning Trajectories (DART), a novel data adaptation framework that bridges the capability gap between expert reasoning trajectories and diverse SLMs. Instead of uniformly imitating expert st","authors_text":"Binbin Lin, Chen Binhui, Ke Li, Ping Li, Weihang Pan, Yong Wu","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2025-05-27T04:08:11Z","title":"Beyond Templates: Dynamic Adaptation of Reasoning Demonstrations via Feasibility-Aware Exploration"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2505.20700","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":"sha256:688f085b33ae5043e7e00aab2471aec68f88009f1d2d24139051dfe22acd61fa","target":"record","created_at":"2026-07-05T11:10:17Z","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":"e24db3450d2c709b320f491f63357c87ac67e76a89360d156191c4f27f7509c8","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2025-05-27T04:08:11Z","title_canon_sha256":"6668252c4af9d652488f4daebcaf56f976ddcf3808c30d8da3cdc403a324d71e"},"schema_version":"1.0","source":{"id":"2505.20700","kind":"arxiv","version":1}},"canonical_sha256":"83427d45b33db6c0ce43ae2544caa74b1fd20f5e019b36d1f6e03afa9b6b7f9c","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"83427d45b33db6c0ce43ae2544caa74b1fd20f5e019b36d1f6e03afa9b6b7f9c","first_computed_at":"2026-07-05T11:10:17.136721Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:10:17.136721Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"/JbTHnOxGFpYWoKICWpSepPO4Ys/yZkCO5sluBHt3Wv0dhhyEhb4VJJC46pyN5m5WSpd/DKnyUyW8pIDD0sDBw==","signature_status":"signed_v1","signed_at":"2026-07-05T11:10:17.137209Z","signed_message":"canonical_sha256_bytes"},"source_id":"2505.20700","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:688f085b33ae5043e7e00aab2471aec68f88009f1d2d24139051dfe22acd61fa","sha256:95c2e33ded569fe82a8b5b63a587f1b2fe479ed985c89d32953424f2f9805347"],"state_sha256":"5c1369e0e52a61c5f24ff45ad933df0abc25c5d6ec2d9f42fdede2b21cfd9740"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"YL48YJKhrMVDF0TJKGhHJ6Oq8VWD+ABRFkbVLiXIpTcVxMN05D2lnYaidWOHRrtEnJDAgVOzRrGLnBZaOuPDBQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-08T06:44:06.412246Z","bundle_sha256":"d3da9f70d8eee911e2b31c5720a0e3583b24bd4a6485f1939ed5d5ff6f865713"}}