{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2025:QOR2JUMELOUQNPDEOHKSY7ZOFA","short_pith_number":"pith:QOR2JUME","schema_version":"1.0","canonical_sha256":"83a3a4d1845ba906bc6471d52c7f2e28385e9bed20137954032e27bca6983d35","source":{"kind":"arxiv","id":"2504.08542","version":1},"attestation_state":"computed","paper":{"title":"Discriminator-Free Direct Preference Optimization for Video Diffusion","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Boxi Wu, Haoran Cheng, Jinghui Xie, Liang Peng, Qide Dong, Shilei Wen, Weiguo Feng, Xiaofei He, Zhao Song, Zhizhou Sha","submitted_at":"2025-04-11T13:55:48Z","abstract_excerpt":"Direct Preference Optimization (DPO), which aligns models with human preferences through win/lose data pairs, has achieved remarkable success in language and image generation. However, applying DPO to video diffusion models faces critical challenges: (1) Data inefficiency. Generating thousands of videos per DPO iteration incurs prohibitive costs; (2) Evaluation uncertainty. Human annotations suffer from subjective bias, and automated discriminators fail to detect subtle temporal artifacts like flickering or motion incoherence. To address these, we propose a discriminator-free video DPO framewo"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2504.08542","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2025-04-11T13:55:48Z","cross_cats_sorted":[],"title_canon_sha256":"841cf1d94fd8ea1c78eff8a65f5477b22609a7cee9b6758e221b6a3c7f05f9e2","abstract_canon_sha256":"a8515d307178915b8862519cce96fbaef524dcd1f2a9e313713870394d1ae4f5"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T10:47:50.580565Z","signature_b64":"CF6JrbdGSYS/wkl4XX7yGoDbXxZrQTlZkUdRjlvzXlmSaVx27mieXHtNl8O5u/f1RjT6p18yTum/kNPf2nmoBg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"83a3a4d1845ba906bc6471d52c7f2e28385e9bed20137954032e27bca6983d35","last_reissued_at":"2026-07-05T10:47:50.580135Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T10:47:50.580135Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Discriminator-Free Direct Preference Optimization for Video Diffusion","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Boxi Wu, Haoran Cheng, Jinghui Xie, Liang Peng, Qide Dong, Shilei Wen, Weiguo Feng, Xiaofei He, Zhao Song, Zhizhou Sha","submitted_at":"2025-04-11T13:55:48Z","abstract_excerpt":"Direct Preference Optimization (DPO), which aligns models with human preferences through win/lose data pairs, has achieved remarkable success in language and image generation. However, applying DPO to video diffusion models faces critical challenges: (1) Data inefficiency. Generating thousands of videos per DPO iteration incurs prohibitive costs; (2) Evaluation uncertainty. Human annotations suffer from subjective bias, and automated discriminators fail to detect subtle temporal artifacts like flickering or motion incoherence. To address these, we propose a discriminator-free video DPO framewo"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2504.08542","kind":"arxiv","version":1},"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/2504.08542/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"},"aliases":[{"alias_kind":"arxiv","alias_value":"2504.08542","created_at":"2026-07-05T10:47:50.580196+00:00"},{"alias_kind":"arxiv_version","alias_value":"2504.08542v1","created_at":"2026-07-05T10:47:50.580196+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2504.08542","created_at":"2026-07-05T10:47:50.580196+00:00"},{"alias_kind":"pith_short_12","alias_value":"QOR2JUMELOUQ","created_at":"2026-07-05T10:47:50.580196+00:00"},{"alias_kind":"pith_short_16","alias_value":"QOR2JUMELOUQNPDE","created_at":"2026-07-05T10:47:50.580196+00:00"},{"alias_kind":"pith_short_8","alias_value":"QOR2JUME","created_at":"2026-07-05T10:47:50.580196+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/QOR2JUMELOUQNPDEOHKSY7ZOFA","json":"https://pith.science/pith/QOR2JUMELOUQNPDEOHKSY7ZOFA.json","graph_json":"https://pith.science/api/pith-number/QOR2JUMELOUQNPDEOHKSY7ZOFA/graph.json","events_json":"https://pith.science/api/pith-number/QOR2JUMELOUQNPDEOHKSY7ZOFA/events.json","paper":"https://pith.science/paper/QOR2JUME"},"agent_actions":{"view_html":"https://pith.science/pith/QOR2JUMELOUQNPDEOHKSY7ZOFA","download_json":"https://pith.science/pith/QOR2JUMELOUQNPDEOHKSY7ZOFA.json","view_paper":"https://pith.science/paper/QOR2JUME","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2504.08542&json=true","fetch_graph":"https://pith.science/api/pith-number/QOR2JUMELOUQNPDEOHKSY7ZOFA/graph.json","fetch_events":"https://pith.science/api/pith-number/QOR2JUMELOUQNPDEOHKSY7ZOFA/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/QOR2JUMELOUQNPDEOHKSY7ZOFA/action/timestamp_anchor","attest_storage":"https://pith.science/pith/QOR2JUMELOUQNPDEOHKSY7ZOFA/action/storage_attestation","attest_author":"https://pith.science/pith/QOR2JUMELOUQNPDEOHKSY7ZOFA/action/author_attestation","sign_citation":"https://pith.science/pith/QOR2JUMELOUQNPDEOHKSY7ZOFA/action/citation_signature","submit_replication":"https://pith.science/pith/QOR2JUMELOUQNPDEOHKSY7ZOFA/action/replication_record"}},"created_at":"2026-07-05T10:47:50.580196+00:00","updated_at":"2026-07-05T10:47:50.580196+00:00"}