{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:MKVLOMPPP2RBPXQACF4YPBHM2U","short_pith_number":"pith:MKVLOMPP","canonical_record":{"source":{"id":"2508.04324","kind":"arxiv","version":4},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2025-08-06T11:10:39Z","cross_cats_sorted":[],"title_canon_sha256":"6de3a96109dfeac090c1bfdc441f39f1288a4549c8d44e9b0d50f438c07d94c8","abstract_canon_sha256":"7c8d6a920e5527a95130b88e1512ceeb717cd047c2ec00aa2e65a98a0236ed89"},"schema_version":"1.0"},"canonical_sha256":"62aab731ef7ea217de0011798784ecd52cdd7a6e318671dc438dda2899051239","source":{"kind":"arxiv","id":"2508.04324","version":4},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2508.04324","created_at":"2026-05-21T21:45:38Z"},{"alias_kind":"arxiv_version","alias_value":"2508.04324v4","created_at":"2026-05-21T21:45:38Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2508.04324","created_at":"2026-05-21T21:45:38Z"},{"alias_kind":"pith_short_12","alias_value":"MKVLOMPPP2RB","created_at":"2026-05-21T21:45:38Z"},{"alias_kind":"pith_short_16","alias_value":"MKVLOMPPP2RBPXQA","created_at":"2026-05-21T21:45:38Z"},{"alias_kind":"pith_short_8","alias_value":"MKVLOMPP","created_at":"2026-05-21T21:45:38Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:MKVLOMPPP2RBPXQACF4YPBHM2U","target":"record","payload":{"canonical_record":{"source":{"id":"2508.04324","kind":"arxiv","version":4},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2025-08-06T11:10:39Z","cross_cats_sorted":[],"title_canon_sha256":"6de3a96109dfeac090c1bfdc441f39f1288a4549c8d44e9b0d50f438c07d94c8","abstract_canon_sha256":"7c8d6a920e5527a95130b88e1512ceeb717cd047c2ec00aa2e65a98a0236ed89"},"schema_version":"1.0"},"canonical_sha256":"62aab731ef7ea217de0011798784ecd52cdd7a6e318671dc438dda2899051239","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-21T21:45:38.093040Z","signature_b64":"axhPsVERPwD6NVk+UMOcDR47HVYPqeWlN/zS8ZjdIbKKRW+yuxb7Xd3JNCL+DMYjbN9obuS/zEPOsSvHFOQeAg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"62aab731ef7ea217de0011798784ecd52cdd7a6e318671dc438dda2899051239","last_reissued_at":"2026-05-21T21:45:38.091232Z","signature_status":"signed_v1","first_computed_at":"2026-05-21T21:45:38.091232Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2508.04324","source_version":4,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-05-21T21:45:38Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"+zxodnZVu2ki8buZ1ou+DqFkRf9jKR5QphNfvmdOG5nCOcnOfWAYPwUdUw7kgs9yosjwv8ucKYiR1d6NHdiGBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-23T03:45:47.248067Z"},"content_sha256":"be6653b78fda783d1e9891d5dca74280cd3558da39d9dbaa1e96e7082c7b8510","schema_version":"1.0","event_id":"sha256:be6653b78fda783d1e9891d5dca74280cd3558da39d9dbaa1e96e7082c7b8510"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:MKVLOMPPP2RBPXQACF4YPBHM2U","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"TempFlow-GRPO: When Timing Matters for GRPO in Flow Models","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Bo Zhang, Dacheng Yin, Fengyun Rao, Jian Yang, Siming Fu, Wanli Li, Xiaoxuan He, Yuke Zhao","submitted_at":"2025-08-06T11:10:39Z","abstract_excerpt":"Recent flow matching models for text-to-image generation have achieved remarkable quality, yet their integration with reinforcement learning for human preference alignment remains suboptimal, hindering fine-grained reward-based optimization. We observe that the key impediment to effective GRPO training of flow models is the temporal uniformity assumption in existing approaches: sparse terminal rewards with uniform credit assignment fail to capture the varying criticality of decisions across generation timesteps, resulting in inefficient exploration and suboptimal convergence. To remedy this sh"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2508.04324","kind":"arxiv","version":4},"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/2508.04324/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":"2026-05-21T21:45:38Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Mbaw5WIeiKdK7hInc45GH4p7JWqm8xabfqBMC8XRpjJylCjlph4KZbQ/ZqGG2nIiqYgcQntkt+NREUOpDd1GDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-23T03:45:47.248777Z"},"content_sha256":"3a4f9f1df75082b9b91ed50df27f065f1fa6649a22577f7df23c7f89b0dc13c5","schema_version":"1.0","event_id":"sha256:3a4f9f1df75082b9b91ed50df27f065f1fa6649a22577f7df23c7f89b0dc13c5"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/MKVLOMPPP2RBPXQACF4YPBHM2U/bundle.json","state_url":"https://pith.science/pith/MKVLOMPPP2RBPXQACF4YPBHM2U/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/MKVLOMPPP2RBPXQACF4YPBHM2U/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":"2026-05-23T03:45:47Z","links":{"resolver":"https://pith.science/pith/MKVLOMPPP2RBPXQACF4YPBHM2U","bundle":"https://pith.science/pith/MKVLOMPPP2RBPXQACF4YPBHM2U/bundle.json","state":"https://pith.science/pith/MKVLOMPPP2RBPXQACF4YPBHM2U/state.json","well_known_bundle":"https://pith.science/.well-known/pith/MKVLOMPPP2RBPXQACF4YPBHM2U/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:MKVLOMPPP2RBPXQACF4YPBHM2U","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":"7c8d6a920e5527a95130b88e1512ceeb717cd047c2ec00aa2e65a98a0236ed89","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2025-08-06T11:10:39Z","title_canon_sha256":"6de3a96109dfeac090c1bfdc441f39f1288a4549c8d44e9b0d50f438c07d94c8"},"schema_version":"1.0","source":{"id":"2508.04324","kind":"arxiv","version":4}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2508.04324","created_at":"2026-05-21T21:45:38Z"},{"alias_kind":"arxiv_version","alias_value":"2508.04324v4","created_at":"2026-05-21T21:45:38Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2508.04324","created_at":"2026-05-21T21:45:38Z"},{"alias_kind":"pith_short_12","alias_value":"MKVLOMPPP2RB","created_at":"2026-05-21T21:45:38Z"},{"alias_kind":"pith_short_16","alias_value":"MKVLOMPPP2RBPXQA","created_at":"2026-05-21T21:45:38Z"},{"alias_kind":"pith_short_8","alias_value":"MKVLOMPP","created_at":"2026-05-21T21:45:38Z"}],"graph_snapshots":[{"event_id":"sha256:3a4f9f1df75082b9b91ed50df27f065f1fa6649a22577f7df23c7f89b0dc13c5","target":"graph","created_at":"2026-05-21T21:45:38Z","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/2508.04324/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Recent flow matching models for text-to-image generation have achieved remarkable quality, yet their integration with reinforcement learning for human preference alignment remains suboptimal, hindering fine-grained reward-based optimization. We observe that the key impediment to effective GRPO training of flow models is the temporal uniformity assumption in existing approaches: sparse terminal rewards with uniform credit assignment fail to capture the varying criticality of decisions across generation timesteps, resulting in inefficient exploration and suboptimal convergence. To remedy this sh","authors_text":"Bo Zhang, Dacheng Yin, Fengyun Rao, Jian Yang, Siming Fu, Wanli Li, Xiaoxuan He, Yuke Zhao","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2025-08-06T11:10:39Z","title":"TempFlow-GRPO: When Timing Matters for GRPO in Flow Models"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2508.04324","kind":"arxiv","version":4},"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:be6653b78fda783d1e9891d5dca74280cd3558da39d9dbaa1e96e7082c7b8510","target":"record","created_at":"2026-05-21T21:45:38Z","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":"7c8d6a920e5527a95130b88e1512ceeb717cd047c2ec00aa2e65a98a0236ed89","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2025-08-06T11:10:39Z","title_canon_sha256":"6de3a96109dfeac090c1bfdc441f39f1288a4549c8d44e9b0d50f438c07d94c8"},"schema_version":"1.0","source":{"id":"2508.04324","kind":"arxiv","version":4}},"canonical_sha256":"62aab731ef7ea217de0011798784ecd52cdd7a6e318671dc438dda2899051239","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"62aab731ef7ea217de0011798784ecd52cdd7a6e318671dc438dda2899051239","first_computed_at":"2026-05-21T21:45:38.091232Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-21T21:45:38.091232Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"axhPsVERPwD6NVk+UMOcDR47HVYPqeWlN/zS8ZjdIbKKRW+yuxb7Xd3JNCL+DMYjbN9obuS/zEPOsSvHFOQeAg==","signature_status":"signed_v1","signed_at":"2026-05-21T21:45:38.093040Z","signed_message":"canonical_sha256_bytes"},"source_id":"2508.04324","source_kind":"arxiv","source_version":4}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:be6653b78fda783d1e9891d5dca74280cd3558da39d9dbaa1e96e7082c7b8510","sha256:3a4f9f1df75082b9b91ed50df27f065f1fa6649a22577f7df23c7f89b0dc13c5"],"state_sha256":"b94060a0093ad2882f233784d70521e5fc18a02a4136fcb96e8584b391078af4"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"+FYCMqppuY1Ks5EH3fPmzpFEdbfhpkx3Or3HnHvjkE7jNxE5lb/IGTTzVMt+oh1B20hcG5sFw/M9/z5yC0hsCA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-23T03:45:47.252250Z","bundle_sha256":"314e415fabda5adf2516f507baf9760cbc1da6e211461351e6fc23ba9f725916"}}