{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:J7TWO3BPTIEFT2DXSRGZNZWADA","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":"11a89db61c47b025f3fac3326283dcbef3d4dfb01561befdad5140c7a0d3a8d5","cross_cats_sorted":["cs.AI","cs.CL"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2026-06-15T09:58:21Z","title_canon_sha256":"7ace83169df8cb3de711d53aaec087795178587464af2a3a14433e07feaf1b7a"},"schema_version":"1.0","source":{"id":"2606.16497","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2606.16497","created_at":"2026-06-25T01:17:55Z"},{"alias_kind":"arxiv_version","alias_value":"2606.16497v2","created_at":"2026-06-25T01:17:55Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2606.16497","created_at":"2026-06-25T01:17:55Z"},{"alias_kind":"pith_short_12","alias_value":"J7TWO3BPTIEF","created_at":"2026-06-25T01:17:55Z"},{"alias_kind":"pith_short_16","alias_value":"J7TWO3BPTIEFT2DX","created_at":"2026-06-25T01:17:55Z"},{"alias_kind":"pith_short_8","alias_value":"J7TWO3BP","created_at":"2026-06-25T01:17:55Z"}],"graph_snapshots":[{"event_id":"sha256:b075b2022f3d2381476c99d3174f2da497d47f30ce279a4dead23c5f7c23998a","target":"graph","created_at":"2026-06-25T01:17:55Z","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/2606.16497/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"GPU kernel optimization represents a paradigm where functional correctness is assumed and execution efficiency is the objective. We present daVinci-kernel, a reinforcement learning framework that couples skill discovery with skill exploitation through a dynamically evolving skill library. daVinci-kernel jointly trains three agents sharing one LLM backbone: a Skill Selection Agent that retrieves relevant techniques via BM25 and LLM reranking, a Policy Agent that generates multi-turn CUDA/Triton kernels conditioned on selected skills, and a Skill Summary Agent that distills successful rollouts i","authors_text":"Dayuan Fu, Dian Yang, Jiarui Hu, Jinlong Hou, Liming Liu, Mohan Jiang, Pengfei Liu, Tongyu Wang","cross_cats":["cs.AI","cs.CL"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2026-06-15T09:58:21Z","title":"daVinci-kernel: Co-Evolving Skill Selection, Summarization, and Utilization via RL for GPU Kernel Optimization"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2606.16497","kind":"arxiv","version":2},"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":"sha256:55a3493af86780be0e89fcbf57a7a5a98db911979a2cb94a6af10bab89fcda22","target":"record","created_at":"2026-06-25T01:17:55Z","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":"11a89db61c47b025f3fac3326283dcbef3d4dfb01561befdad5140c7a0d3a8d5","cross_cats_sorted":["cs.AI","cs.CL"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2026-06-15T09:58:21Z","title_canon_sha256":"7ace83169df8cb3de711d53aaec087795178587464af2a3a14433e07feaf1b7a"},"schema_version":"1.0","source":{"id":"2606.16497","kind":"arxiv","version":2}},"canonical_sha256":"4fe7676c2f9a0859e877944d96e6c018093c46d3d1c4686af6be5597f4023a3c","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"4fe7676c2f9a0859e877944d96e6c018093c46d3d1c4686af6be5597f4023a3c","first_computed_at":"2026-06-25T01:17:55.112881Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-06-25T01:17:55.112881Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"8iBDEOSKLH0yAVndiMTnJoN2mMI7yo2MOCB54AKV5KjzC4B3N+TI/yZJ1TAQI4HAeE+xnpfmx7PoU5unnRuFBQ==","signature_status":"signed_v1","signed_at":"2026-06-25T01:17:55.113250Z","signed_message":"canonical_sha256_bytes"},"source_id":"2606.16497","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:55a3493af86780be0e89fcbf57a7a5a98db911979a2cb94a6af10bab89fcda22","sha256:b075b2022f3d2381476c99d3174f2da497d47f30ce279a4dead23c5f7c23998a"],"state_sha256":"038eca5500a7d84ddbd740e74d72c51a3c545f71f1cbb6ad12fb573431cfd41b"}