{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:P6JO5JMCBFN5KF67DQRZC264HT","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":"8621b21fde8675a7548907e70f29f174a80607e696777b6a43d4333cde52fc35","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2023-12-07T18:43:45Z","title_canon_sha256":"efa8395d3003f4f17b413e4f6c9e2a8ef91e61974ff84e2c9919693d6354b358"},"schema_version":"1.0","source":{"id":"2312.04524","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2312.04524","created_at":"2026-07-05T07:21:35Z"},{"alias_kind":"arxiv_version","alias_value":"2312.04524v1","created_at":"2026-07-05T07:21:35Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2312.04524","created_at":"2026-07-05T07:21:35Z"},{"alias_kind":"pith_short_12","alias_value":"P6JO5JMCBFN5","created_at":"2026-07-05T07:21:35Z"},{"alias_kind":"pith_short_16","alias_value":"P6JO5JMCBFN5KF67","created_at":"2026-07-05T07:21:35Z"},{"alias_kind":"pith_short_8","alias_value":"P6JO5JMC","created_at":"2026-07-05T07:21:35Z"}],"graph_snapshots":[{"event_id":"sha256:46d81cf8e940cb6cad1e6400f67a3baf9ea0cc3b75ebac57afe50f9aada66e73","target":"graph","created_at":"2026-07-05T07:21:35Z","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/2312.04524/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Recent advancements in diffusion-based models have demonstrated significant success in generating images from text. However, video editing models have not yet reached the same level of visual quality and user control. To address this, we introduce RAVE, a zero-shot video editing method that leverages pre-trained text-to-image diffusion models without additional training. RAVE takes an input video and a text prompt to produce high-quality videos while preserving the original motion and semantic structure. It employs a novel noise shuffling strategy, leveraging spatio-temporal interactions betwe","authors_text":"Bariscan Kurtkaya, Hidir Yesiltepe, James M. Rehg, Ozgur Kara, Pinar Yanardag","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2023-12-07T18:43:45Z","title":"RAVE: Randomized Noise Shuffling for Fast and Consistent Video Editing with Diffusion Models"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2312.04524","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":"sha256:8814097d8bb897cfb6f78842cb4c537e927a4d55a25ceea46df375e9d052e6e9","target":"record","created_at":"2026-07-05T07:21:35Z","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":"8621b21fde8675a7548907e70f29f174a80607e696777b6a43d4333cde52fc35","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2023-12-07T18:43:45Z","title_canon_sha256":"efa8395d3003f4f17b413e4f6c9e2a8ef91e61974ff84e2c9919693d6354b358"},"schema_version":"1.0","source":{"id":"2312.04524","kind":"arxiv","version":1}},"canonical_sha256":"7f92eea582095bd517df1c23916bdc3ce55928d55f41a0439885d0679879d4d3","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"7f92eea582095bd517df1c23916bdc3ce55928d55f41a0439885d0679879d4d3","first_computed_at":"2026-07-05T07:21:35.504570Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T07:21:35.504570Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"R2IAZYdCwWEcN2BjSvnUEMyNrj7MaROqwhZ7sSnOKexevna5gSIvXerlcH05v5848HztnKD5vi9uA7HuN5ilBg==","signature_status":"signed_v1","signed_at":"2026-07-05T07:21:35.505057Z","signed_message":"canonical_sha256_bytes"},"source_id":"2312.04524","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:8814097d8bb897cfb6f78842cb4c537e927a4d55a25ceea46df375e9d052e6e9","sha256:46d81cf8e940cb6cad1e6400f67a3baf9ea0cc3b75ebac57afe50f9aada66e73"],"state_sha256":"fceb2e06e58ca57980b390c5c916f0f023e5b3ec23501c29bc10992a0b60f3ab"}