{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:G6HLRYCYAGMZL2QOJ3JWNMAYBL","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":"296d181e3f1efa597eb0210f3efa53b87347bf9d98ce9a58d4d69497d68aaae2","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2026-07-19T13:32:54Z","title_canon_sha256":"df46f1ff423f735c4c8eb335bc73dd2b4bf5de544743e19a1b6730074705c929"},"schema_version":"1.0","source":{"id":"2607.17247","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2607.17247","created_at":"2026-07-21T01:21:23Z"},{"alias_kind":"arxiv_version","alias_value":"2607.17247v1","created_at":"2026-07-21T01:21:23Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2607.17247","created_at":"2026-07-21T01:21:23Z"},{"alias_kind":"pith_short_12","alias_value":"G6HLRYCYAGMZ","created_at":"2026-07-21T01:21:23Z"},{"alias_kind":"pith_short_16","alias_value":"G6HLRYCYAGMZL2QO","created_at":"2026-07-21T01:21:23Z"},{"alias_kind":"pith_short_8","alias_value":"G6HLRYCY","created_at":"2026-07-21T01:21:23Z"}],"graph_snapshots":[{"event_id":"sha256:8dd4bec928bfbfd485c1b0dae3781aa4ef2a5b7644593ba7ca74314e488a4e9c","target":"graph","created_at":"2026-07-21T01:21:23Z","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/2607.17247/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Large language model (LLM) post-training is essential for improving reasoning, adaptation, and alignment. Existing methods mainly follow two paradigms: reinforcement learning (RL) and on-policy distillation (OPD). However, RL relies on coarse-grained outcome supervision, resulting in difficult credit assignment and limited capability to acquire new knowledge. OPD, meanwhile, unconditionally matches teacher logits through KL divergence, which creates a dilemma: similar teachers provide little new knowledge, while substantially different teachers often yield ineffective guidance, largely restric","authors_text":"Chen Wang, Ge Lan, Hexuan Deng, Jionghao Bai, Yining Zhang, Yue Wang, Zhaochun Li","cross_cats":["cs.AI"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2026-07-19T13:32:54Z","title":"Distilled Reinforcement Learning for LLM Post-training"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2607.17247","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":"sha256:23735b2bf91754a3c7b4e05aab21df9602ce1b7781bc4f4737b63b461faaa71a","target":"record","created_at":"2026-07-21T01:21:23Z","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":"296d181e3f1efa597eb0210f3efa53b87347bf9d98ce9a58d4d69497d68aaae2","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2026-07-19T13:32:54Z","title_canon_sha256":"df46f1ff423f735c4c8eb335bc73dd2b4bf5de544743e19a1b6730074705c929"},"schema_version":"1.0","source":{"id":"2607.17247","kind":"arxiv","version":1}},"canonical_sha256":"378eb8e058019995ea0e4ed366b0180ae942cfb87fec7386ca1fb364fd90009d","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"378eb8e058019995ea0e4ed366b0180ae942cfb87fec7386ca1fb364fd90009d","first_computed_at":"2026-07-21T01:21:23.745644Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-21T01:21:23.745644Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"B8Izm/9F2uF0+W10U5am+Cn/4go9Brn38MCaB8qRmTBkcTkTykdXRPa5zQKBELbowSlTxWTZdnqk+dKIxuebAA==","signature_status":"signed_v1","signed_at":"2026-07-21T01:21:23.746478Z","signed_message":"canonical_sha256_bytes"},"source_id":"2607.17247","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:23735b2bf91754a3c7b4e05aab21df9602ce1b7781bc4f4737b63b461faaa71a","sha256:8dd4bec928bfbfd485c1b0dae3781aa4ef2a5b7644593ba7ca74314e488a4e9c"],"state_sha256":"77e03106e382ff4e5f6e169196d2249119f2aae60786557e2ea79765f2d6183f"}