{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:PI53PQ3VFE6H6G4GTX3NH7ANLX","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":"783e60a59b9e1f8461615db0c44c3a12273e463ae28e149c720a14ac3cb4d0a1","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2025-11-24T03:21:17Z","title_canon_sha256":"8600f52156e4ac63ec5ef2873ae469f3c1927ae8315e3e1f73051ad85bf82aea"},"schema_version":"1.0","source":{"id":"2511.18719","kind":"arxiv","version":4}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2511.18719","created_at":"2026-05-20T00:00:28Z"},{"alias_kind":"arxiv_version","alias_value":"2511.18719v4","created_at":"2026-05-20T00:00:28Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2511.18719","created_at":"2026-05-20T00:00:28Z"},{"alias_kind":"pith_short_12","alias_value":"PI53PQ3VFE6H","created_at":"2026-05-20T00:00:28Z"},{"alias_kind":"pith_short_16","alias_value":"PI53PQ3VFE6H6G4G","created_at":"2026-05-20T00:00:28Z"},{"alias_kind":"pith_short_8","alias_value":"PI53PQ3V","created_at":"2026-05-20T00:00:28Z"}],"graph_snapshots":[{"event_id":"sha256:d12b12d0eb4ee2bb940fd8ea927f4ffcae3a2cbd806d364ad62646a34ea3bf64","target":"graph","created_at":"2026-05-20T00:00:28Z","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/2511.18719/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Reinforcement learning (RL) has become a powerful tool for post-training visual generative models, with Group Relative Policy Optimization (GRPO) increasingly used to align generators with human preferences. However, existing GRPO pipelines rely on a single scalar reward per sample, treating each image or video as a holistic entity and ignoring the rich spatial and temporal structure of visual content. This coarse supervision hinders the correction of localized artifacts and the modeling of fine-grained perceptual cues. We introduce Visual Preference Policy Optimization (ViPO), a GRPO variant ","authors_text":"Chi Zhang, Haibin Huang, Rui Li, Xuelong Li, Yi Zhou, Yuanzhi Liang, Ziqi Ni","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2025-11-24T03:21:17Z","title":"Seeing What Matters: Visual Preference Policy Optimization for Visual Generation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2511.18719","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":"sha256:8d9aa457814d55b91b764fe28c773ffe259110324a0d81b4a0ac6bc9998f9e8c","target":"record","created_at":"2026-05-20T00:00:28Z","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":"783e60a59b9e1f8461615db0c44c3a12273e463ae28e149c720a14ac3cb4d0a1","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2025-11-24T03:21:17Z","title_canon_sha256":"8600f52156e4ac63ec5ef2873ae469f3c1927ae8315e3e1f73051ad85bf82aea"},"schema_version":"1.0","source":{"id":"2511.18719","kind":"arxiv","version":4}},"canonical_sha256":"7a3bb7c375293c7f1b869df6d3fc0d5dc7f32ac67fcf303d6eecd6266867bb07","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"7a3bb7c375293c7f1b869df6d3fc0d5dc7f32ac67fcf303d6eecd6266867bb07","first_computed_at":"2026-05-20T00:00:28.454124Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-20T00:00:28.454124Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"6zAL4aTMqEAPVrLrRvCz9Hff0B8IjuCH/9q6GqBwXge3GIh+PKgowk6d8hJihaH0rB/armaGxSX3XQCmYd/dDw==","signature_status":"signed_v1","signed_at":"2026-05-20T00:00:28.454924Z","signed_message":"canonical_sha256_bytes"},"source_id":"2511.18719","source_kind":"arxiv","source_version":4}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:8d9aa457814d55b91b764fe28c773ffe259110324a0d81b4a0ac6bc9998f9e8c","sha256:d12b12d0eb4ee2bb940fd8ea927f4ffcae3a2cbd806d364ad62646a34ea3bf64"],"state_sha256":"ab83beef02c47dc69da131802f8dcc4bfa2cecb57774381f7deac5cf6e68b8ef"}