{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:COW2VO242Q7WJKDTJPDFTWZ5LK","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":"86c621b70455bb819668bc5bd412f8ba80efee82f5cb97edf9af5838e6b680ad","cross_cats_sorted":["cs.AI","cs.CV"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2026-07-01T07:25:11Z","title_canon_sha256":"2c0218aeec0c6f6dc7119d959b777569ea3344255d423f88b9af23e74ac5fa55"},"schema_version":"1.0","source":{"id":"2607.00535","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2607.00535","created_at":"2026-07-02T01:17:46Z"},{"alias_kind":"arxiv_version","alias_value":"2607.00535v1","created_at":"2026-07-02T01:17:46Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2607.00535","created_at":"2026-07-02T01:17:46Z"},{"alias_kind":"pith_short_12","alias_value":"COW2VO242Q7W","created_at":"2026-07-02T01:17:46Z"},{"alias_kind":"pith_short_16","alias_value":"COW2VO242Q7WJKDT","created_at":"2026-07-02T01:17:46Z"},{"alias_kind":"pith_short_8","alias_value":"COW2VO24","created_at":"2026-07-02T01:17:46Z"}],"graph_snapshots":[{"event_id":"sha256:3c877f159adee954fa41fcd9396c6f36b09f593c6b959ed636b59c6499b135be","target":"graph","created_at":"2026-07-02T01:17:46Z","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/2607.00535/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Few-step flow-map generators, such as consistency models and MeanFlow, accelerate sampling by directly learning long-range transport maps between noise and data. However, these models are typically deterministic, which makes them difficult to optimize with reinforcement learning (RL) post-training methods that require stochastic trajectories and well-defined likelihood ratios. Existing SDE-based stochasticization techniques are designed for velocity-based samplers with infinitesimal or finely discretized transitions, and therefore do not directly apply to long-range flow maps. In this work, we","authors_text":"Bo Zhu, Wen Zhang, Zhiqi Li","cross_cats":["cs.AI","cs.CV"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2026-07-01T07:25:11Z","title":"Flow-Map GRPO: Reinforcement Learning for Few-Step Flow-Map Generators via Anchored Stochastic Composition"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2607.00535","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:d29c9111b10233825e4427c4dcb60f6194dfa049d177558247ffce0b046debb0","target":"record","created_at":"2026-07-02T01:17:46Z","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":"86c621b70455bb819668bc5bd412f8ba80efee82f5cb97edf9af5838e6b680ad","cross_cats_sorted":["cs.AI","cs.CV"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2026-07-01T07:25:11Z","title_canon_sha256":"2c0218aeec0c6f6dc7119d959b777569ea3344255d423f88b9af23e74ac5fa55"},"schema_version":"1.0","source":{"id":"2607.00535","kind":"arxiv","version":1}},"canonical_sha256":"13adaabb5cd43f64a8734bc659db3d5aaa72505bc32bdd1a3552d5ff5b9b2f12","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"13adaabb5cd43f64a8734bc659db3d5aaa72505bc32bdd1a3552d5ff5b9b2f12","first_computed_at":"2026-07-02T01:17:46.929423Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-02T01:17:46.929423Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"UdumaMPueOHxQGkbf2eMNHmThzvNU1J5FA6lZUxR9NnoO4BMi/R0GfwVLr72n81csxpSmvBlGmVrLe8Y6rKKAA==","signature_status":"signed_v1","signed_at":"2026-07-02T01:17:46.929805Z","signed_message":"canonical_sha256_bytes"},"source_id":"2607.00535","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:d29c9111b10233825e4427c4dcb60f6194dfa049d177558247ffce0b046debb0","sha256:3c877f159adee954fa41fcd9396c6f36b09f593c6b959ed636b59c6499b135be"],"state_sha256":"0a34f680362bff258f80f76e1c518c404ede416f1fff85acc7b856723c0b6fd8"}