{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:FAIAUE5U2IK4OMGENZQ7Z7HFIZ","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":"bbc4a64fdc4d9a7ae6817cb73df1bd42bb10401e35800df0aefc3b905944b6bd","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2022-11-22T20:39:18Z","title_canon_sha256":"e728943b7f60580a26e95cb719a6cd84737996e8aa4571040a0bbc1edc118f77"},"schema_version":"1.0","source":{"id":"2211.12572","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2211.12572","created_at":"2026-07-05T05:18:52Z"},{"alias_kind":"arxiv_version","alias_value":"2211.12572v1","created_at":"2026-07-05T05:18:52Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2211.12572","created_at":"2026-07-05T05:18:52Z"},{"alias_kind":"pith_short_12","alias_value":"FAIAUE5U2IK4","created_at":"2026-07-05T05:18:52Z"},{"alias_kind":"pith_short_16","alias_value":"FAIAUE5U2IK4OMGE","created_at":"2026-07-05T05:18:52Z"},{"alias_kind":"pith_short_8","alias_value":"FAIAUE5U","created_at":"2026-07-05T05:18:52Z"}],"graph_snapshots":[{"event_id":"sha256:19c206e50983ef6dfb1395a8eeb0dfc2f60a9616952ccf5aa3fee6a18079eba1","target":"graph","created_at":"2026-07-05T05:18:52Z","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/2211.12572/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Large-scale text-to-image generative models have been a revolutionary breakthrough in the evolution of generative AI, allowing us to synthesize diverse images that convey highly complex visual concepts. However, a pivotal challenge in leveraging such models for real-world content creation tasks is providing users with control over the generated content. In this paper, we present a new framework that takes text-to-image synthesis to the realm of image-to-image translation -- given a guidance image and a target text prompt, our method harnesses the power of a pre-trained text-to-image diffusion ","authors_text":"Michal Geyer, Narek Tumanyan, Shai Bagon, Tali Dekel","cross_cats":["cs.AI"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2022-11-22T20:39:18Z","title":"Plug-and-Play Diffusion Features for Text-Driven Image-to-Image Translation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2211.12572","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":"sha256:581f09c0e8f327e0ae882c8a3dea62bd3b9a98d696112210bbbb5d7ccf4964f8","target":"record","created_at":"2026-07-05T05:18:52Z","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":"bbc4a64fdc4d9a7ae6817cb73df1bd42bb10401e35800df0aefc3b905944b6bd","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2022-11-22T20:39:18Z","title_canon_sha256":"e728943b7f60580a26e95cb719a6cd84737996e8aa4571040a0bbc1edc118f77"},"schema_version":"1.0","source":{"id":"2211.12572","kind":"arxiv","version":1}},"canonical_sha256":"28100a13b4d215c730c46e61fcfce5465ab168d9a33917d321bc3804539769dc","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"28100a13b4d215c730c46e61fcfce5465ab168d9a33917d321bc3804539769dc","first_computed_at":"2026-07-05T05:18:52.425514Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T05:18:52.425514Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"GSp9gbNFPfcgwu9QcoGB8Ry63yBZ6S+TfS2nHeqTR9N+7sHejZ4k7w+8aoRQXDrNJdSojF7tLcj8eqO0jeGODw==","signature_status":"signed_v1","signed_at":"2026-07-05T05:18:52.425940Z","signed_message":"canonical_sha256_bytes"},"source_id":"2211.12572","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:581f09c0e8f327e0ae882c8a3dea62bd3b9a98d696112210bbbb5d7ccf4964f8","sha256:19c206e50983ef6dfb1395a8eeb0dfc2f60a9616952ccf5aa3fee6a18079eba1"],"state_sha256":"74be4dc94aa076387171ab88d5c2f00c3d54bed9d5b494dda0a64ffd5a7b2cf6"}