{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:BNWLEHSOGZ3DWOIIKVVPUK4NPN","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":"801010777d06b48fe6d699e50a180f6c9bf8583c7f632766bc1dcd198b614933","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.CV","submitted_at":"2024-07-31T07:54:26Z","title_canon_sha256":"18a06bd0c94c2cbb2f2493a7bacb87cd49999873c60ed28fac3fa8410bea4efe"},"schema_version":"1.0","source":{"id":"2407.21408","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2407.21408","created_at":"2026-07-05T09:54:03Z"},{"alias_kind":"arxiv_version","alias_value":"2407.21408v2","created_at":"2026-07-05T09:54:03Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2407.21408","created_at":"2026-07-05T09:54:03Z"},{"alias_kind":"pith_short_12","alias_value":"BNWLEHSOGZ3D","created_at":"2026-07-05T09:54:03Z"},{"alias_kind":"pith_short_16","alias_value":"BNWLEHSOGZ3DWOII","created_at":"2026-07-05T09:54:03Z"},{"alias_kind":"pith_short_8","alias_value":"BNWLEHSO","created_at":"2026-07-05T09:54:03Z"}],"graph_snapshots":[{"event_id":"sha256:f454dbd90ac9d785cadd2b6f0f5b52e8733306b8558c0f90437bef41adcf0cd7","target":"graph","created_at":"2026-07-05T09:54:03Z","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/2407.21408/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"In recent years, artificial intelligence (AI)-driven video generation has gained significant attention. Consequently, there is a growing need for accurate video quality assessment (VQA) metrics to evaluate the perceptual quality of AI-generated content (AIGC) videos and optimize video generation models. However, assessing the quality of AIGC videos remains a significant challenge because these videos often exhibit highly complex distortions, such as unnatural actions and irrational objects. To address this challenge, we systematically investigate the AIGC-VQA problem, considering both subjecti","authors_text":"Chunyi Li, Fengyu Sun, Guangtao Zhai, Jun Jia, Puyi Wang, Shangling Jui, Wei Sun, Xinyue Li, Xiongkuo Min, Zhichao Zhang, Zicheng Zhang, Zijian Chen","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.CV","submitted_at":"2024-07-31T07:54:26Z","title":"Benchmarking Multi-dimensional AIGC Video Quality Assessment: A Dataset and Unified Model"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2407.21408","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:c8fe2e7ee7696fd6539277e6733ed47e4543a30756de75e55f42d69dd0dbf0d9","target":"record","created_at":"2026-07-05T09:54:03Z","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":"801010777d06b48fe6d699e50a180f6c9bf8583c7f632766bc1dcd198b614933","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.CV","submitted_at":"2024-07-31T07:54:26Z","title_canon_sha256":"18a06bd0c94c2cbb2f2493a7bacb87cd49999873c60ed28fac3fa8410bea4efe"},"schema_version":"1.0","source":{"id":"2407.21408","kind":"arxiv","version":2}},"canonical_sha256":"0b6cb21e4e36763b3908556afa2b8d7b684008ee52753303fb28ae91a44cb322","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"0b6cb21e4e36763b3908556afa2b8d7b684008ee52753303fb28ae91a44cb322","first_computed_at":"2026-07-05T09:54:03.397412Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:54:03.397412Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"hZz4s8eLF6OrTiy/fxByFcitmm3QjYdAhpO59s9VKTieh1n7IzUhY3suIo3KTLRiU6Qbru4VRzQGq9XdFx8hBA==","signature_status":"signed_v1","signed_at":"2026-07-05T09:54:03.397905Z","signed_message":"canonical_sha256_bytes"},"source_id":"2407.21408","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:c8fe2e7ee7696fd6539277e6733ed47e4543a30756de75e55f42d69dd0dbf0d9","sha256:f454dbd90ac9d785cadd2b6f0f5b52e8733306b8558c0f90437bef41adcf0cd7"],"state_sha256":"6b6a93ace0b430ad363bb0fe8850a0ee89a099a35b266dc0a412c654e8671a3b"}