{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:QF7XK2PEMH35U3BVKA3YO23XGR","short_pith_number":"pith:QF7XK2PE","canonical_record":{"source":{"id":"2505.22543","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2025-05-28T16:24:52Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"5df36f5b46693b4fc1fa22f109c6f7fdd69366d6d04d16570720577cdc60428c","abstract_canon_sha256":"b3f33a58d85c5680d4d1f633576a7189e8feca47897873f0861800f70e5d5e75"},"schema_version":"1.0"},"canonical_sha256":"817f7569e461f7da6c355037876b77347b21475f5b6b206457514e38ccca210e","source":{"kind":"arxiv","id":"2505.22543","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2505.22543","created_at":"2026-07-05T11:11:26Z"},{"alias_kind":"arxiv_version","alias_value":"2505.22543v1","created_at":"2026-07-05T11:11:26Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2505.22543","created_at":"2026-07-05T11:11:26Z"},{"alias_kind":"pith_short_12","alias_value":"QF7XK2PEMH35","created_at":"2026-07-05T11:11:26Z"},{"alias_kind":"pith_short_16","alias_value":"QF7XK2PEMH35U3BV","created_at":"2026-07-05T11:11:26Z"},{"alias_kind":"pith_short_8","alias_value":"QF7XK2PE","created_at":"2026-07-05T11:11:26Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:QF7XK2PEMH35U3BVKA3YO23XGR","target":"record","payload":{"canonical_record":{"source":{"id":"2505.22543","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2025-05-28T16:24:52Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"5df36f5b46693b4fc1fa22f109c6f7fdd69366d6d04d16570720577cdc60428c","abstract_canon_sha256":"b3f33a58d85c5680d4d1f633576a7189e8feca47897873f0861800f70e5d5e75"},"schema_version":"1.0"},"canonical_sha256":"817f7569e461f7da6c355037876b77347b21475f5b6b206457514e38ccca210e","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:11:26.403507Z","signature_b64":"DytHBoHnNnaojG8osx0whxareQ4/fSQUbMmQCqi7LE+V95sxbZOjuBEFFKwA76GuFHpuX4KuGopBbEv15H/lCA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"817f7569e461f7da6c355037876b77347b21475f5b6b206457514e38ccca210e","last_reissued_at":"2026-07-05T11:11:26.402956Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:11:26.402956Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2505.22543","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T11:11:26Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"eZirvHrMkp2sichv3BZE4rbdCvRXqoE3Ocek/seeFwyIoLgenJyC9g390m8GEqMndCbevlQ75RYsPjNxiKfGCw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-08T20:26:13.897161Z"},"content_sha256":"b2bdbce3ae56bb4337eb6fea9492839c27e4125c4ce4bfdcb0891dc77af9f96d","schema_version":"1.0","event_id":"sha256:b2bdbce3ae56bb4337eb6fea9492839c27e4125c4ce4bfdcb0891dc77af9f96d"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:QF7XK2PEMH35U3BVKA3YO23XGR","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Scaling-up Perceptual Video Quality Assessment","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CV","authors_text":"Bin Wang, Chunyi Li, Guangtao Zhai, Guanyu Zhu, Haoning Wu, Haoran Zhang, Jinliang Han, Qiyong Zhao, Xiaohong Liu, Xiaorong Zhu, Xiongkuo Min, Yingji Liang, Zeyu Zhang, Zicheng Zhang, Ziheng Jia","submitted_at":"2025-05-28T16:24:52Z","abstract_excerpt":"The data scaling law has been shown to significantly enhance the performance of large multi-modal models (LMMs) across various downstream tasks. However, in the domain of perceptual video quality assessment (VQA), the potential of scaling law remains unprecedented due to the scarcity of labeled resources and the insufficient scale of datasets. To address this, we propose \\textbf{OmniVQA}, an efficient framework designed to efficiently build high-quality, human-in-the-loop VQA multi-modal instruction databases (MIDBs). We then scale up to create \\textbf{OmniVQA-Chat-400K}, the largest MIDB in t"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2505.22543","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/2505.22543/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":"2026-07-05T11:11:26Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"NNaBTE5KVRzj1EBF97vlevu7L62gwPfI+UVzpsEIPyx31+eQk/dvk/wgcJlbYGjyH/Q3IfDFE9Eq90pzHQiUAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-08T20:26:13.898003Z"},"content_sha256":"d90575be7ae3f419975ad940936eac7b41ec8b534ed53c093ee2014c2e727a2a","schema_version":"1.0","event_id":"sha256:d90575be7ae3f419975ad940936eac7b41ec8b534ed53c093ee2014c2e727a2a"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/QF7XK2PEMH35U3BVKA3YO23XGR/bundle.json","state_url":"https://pith.science/pith/QF7XK2PEMH35U3BVKA3YO23XGR/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/QF7XK2PEMH35U3BVKA3YO23XGR/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":"2026-08-08T20:26:13Z","links":{"resolver":"https://pith.science/pith/QF7XK2PEMH35U3BVKA3YO23XGR","bundle":"https://pith.science/pith/QF7XK2PEMH35U3BVKA3YO23XGR/bundle.json","state":"https://pith.science/pith/QF7XK2PEMH35U3BVKA3YO23XGR/state.json","well_known_bundle":"https://pith.science/.well-known/pith/QF7XK2PEMH35U3BVKA3YO23XGR/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:QF7XK2PEMH35U3BVKA3YO23XGR","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":"b3f33a58d85c5680d4d1f633576a7189e8feca47897873f0861800f70e5d5e75","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2025-05-28T16:24:52Z","title_canon_sha256":"5df36f5b46693b4fc1fa22f109c6f7fdd69366d6d04d16570720577cdc60428c"},"schema_version":"1.0","source":{"id":"2505.22543","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2505.22543","created_at":"2026-07-05T11:11:26Z"},{"alias_kind":"arxiv_version","alias_value":"2505.22543v1","created_at":"2026-07-05T11:11:26Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2505.22543","created_at":"2026-07-05T11:11:26Z"},{"alias_kind":"pith_short_12","alias_value":"QF7XK2PEMH35","created_at":"2026-07-05T11:11:26Z"},{"alias_kind":"pith_short_16","alias_value":"QF7XK2PEMH35U3BV","created_at":"2026-07-05T11:11:26Z"},{"alias_kind":"pith_short_8","alias_value":"QF7XK2PE","created_at":"2026-07-05T11:11:26Z"}],"graph_snapshots":[{"event_id":"sha256:d90575be7ae3f419975ad940936eac7b41ec8b534ed53c093ee2014c2e727a2a","target":"graph","created_at":"2026-07-05T11:11:26Z","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/2505.22543/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"The data scaling law has been shown to significantly enhance the performance of large multi-modal models (LMMs) across various downstream tasks. However, in the domain of perceptual video quality assessment (VQA), the potential of scaling law remains unprecedented due to the scarcity of labeled resources and the insufficient scale of datasets. To address this, we propose \\textbf{OmniVQA}, an efficient framework designed to efficiently build high-quality, human-in-the-loop VQA multi-modal instruction databases (MIDBs). We then scale up to create \\textbf{OmniVQA-Chat-400K}, the largest MIDB in t","authors_text":"Bin Wang, Chunyi Li, Guangtao Zhai, Guanyu Zhu, Haoning Wu, Haoran Zhang, Jinliang Han, Qiyong Zhao, Xiaohong Liu, Xiaorong Zhu, Xiongkuo Min, Yingji Liang, Zeyu Zhang, Zicheng Zhang, Ziheng Jia","cross_cats":["cs.AI"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2025-05-28T16:24:52Z","title":"Scaling-up Perceptual Video Quality Assessment"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2505.22543","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:b2bdbce3ae56bb4337eb6fea9492839c27e4125c4ce4bfdcb0891dc77af9f96d","target":"record","created_at":"2026-07-05T11:11:26Z","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":"b3f33a58d85c5680d4d1f633576a7189e8feca47897873f0861800f70e5d5e75","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2025-05-28T16:24:52Z","title_canon_sha256":"5df36f5b46693b4fc1fa22f109c6f7fdd69366d6d04d16570720577cdc60428c"},"schema_version":"1.0","source":{"id":"2505.22543","kind":"arxiv","version":1}},"canonical_sha256":"817f7569e461f7da6c355037876b77347b21475f5b6b206457514e38ccca210e","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"817f7569e461f7da6c355037876b77347b21475f5b6b206457514e38ccca210e","first_computed_at":"2026-07-05T11:11:26.402956Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:11:26.402956Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"DytHBoHnNnaojG8osx0whxareQ4/fSQUbMmQCqi7LE+V95sxbZOjuBEFFKwA76GuFHpuX4KuGopBbEv15H/lCA==","signature_status":"signed_v1","signed_at":"2026-07-05T11:11:26.403507Z","signed_message":"canonical_sha256_bytes"},"source_id":"2505.22543","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:b2bdbce3ae56bb4337eb6fea9492839c27e4125c4ce4bfdcb0891dc77af9f96d","sha256:d90575be7ae3f419975ad940936eac7b41ec8b534ed53c093ee2014c2e727a2a"],"state_sha256":"43b9466fc99c320477384387037b3449a8d6d9281ef6630799752ecce90a7394"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"f3NjG2AU23S9BQDQ8TR+uHeLMZJVFDgXNsCzpoQxOqm9lCJbDFQp4vWsF+wc7w336R3M1rE3aDrbHkwL9vbmAg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-08T20:26:13.902908Z","bundle_sha256":"bbd72e833355408026793d031871d6c70f08b542567d2572261426e55d5470b3"}}