{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:CTAXE6E6Q2COYMV6FKPCAKFYTD","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":"4709a3742e35124cec3501d0b486b42adcd4c141d1ee58ba6efe94a8f043b06e","cross_cats_sorted":["cs.GR","cs.LG"],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CV","submitted_at":"2023-05-25T17:59:04Z","title_canon_sha256":"c558555dab4efc35100842ad30ac9f460a41f34ab52da89a328c10440ae77297"},"schema_version":"1.0","source":{"id":"2305.16311","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2305.16311","created_at":"2026-07-05T07:23:26Z"},{"alias_kind":"arxiv_version","alias_value":"2305.16311v2","created_at":"2026-07-05T07:23:26Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2305.16311","created_at":"2026-07-05T07:23:26Z"},{"alias_kind":"pith_short_12","alias_value":"CTAXE6E6Q2CO","created_at":"2026-07-05T07:23:26Z"},{"alias_kind":"pith_short_16","alias_value":"CTAXE6E6Q2COYMV6","created_at":"2026-07-05T07:23:26Z"},{"alias_kind":"pith_short_8","alias_value":"CTAXE6E6","created_at":"2026-07-05T07:23:26Z"}],"graph_snapshots":[{"event_id":"sha256:558c33ef3b3cbf0cc1dafea61d70072653511a829299f6cad95da0d4b4f04b90","target":"graph","created_at":"2026-07-05T07:23:26Z","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/2305.16311/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Text-to-image model personalization aims to introduce a user-provided concept to the model, allowing its synthesis in diverse contexts. However, current methods primarily focus on the case of learning a single concept from multiple images with variations in backgrounds and poses, and struggle when adapted to a different scenario. In this work, we introduce the task of textual scene decomposition: given a single image of a scene that may contain several concepts, we aim to extract a distinct text token for each concept, enabling fine-grained control over the generated scenes. To this end, we pr","authors_text":"Daniel Cohen-Or, Dani Lischinski, Kfir Aberman, Ohad Fried, Omri Avrahami","cross_cats":["cs.GR","cs.LG"],"headline":"","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CV","submitted_at":"2023-05-25T17:59:04Z","title":"Break-A-Scene: Extracting Multiple Concepts from a Single Image"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2305.16311","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":"sha256:09e4a765e18029d9efb508076c8ed70a6f2d1534373431b4b6bf834f106338af","target":"record","created_at":"2026-07-05T07:23:26Z","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":"4709a3742e35124cec3501d0b486b42adcd4c141d1ee58ba6efe94a8f043b06e","cross_cats_sorted":["cs.GR","cs.LG"],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CV","submitted_at":"2023-05-25T17:59:04Z","title_canon_sha256":"c558555dab4efc35100842ad30ac9f460a41f34ab52da89a328c10440ae77297"},"schema_version":"1.0","source":{"id":"2305.16311","kind":"arxiv","version":2}},"canonical_sha256":"14c172789e8684ec32be2a9e2028b898e40e136d605c0af70443096e28b17902","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"14c172789e8684ec32be2a9e2028b898e40e136d605c0af70443096e28b17902","first_computed_at":"2026-07-05T07:23:26.388497Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T07:23:26.388497Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"N3FuAUf7ZToKGcczDHBx7ehRjIapx3ivi7ML56XSrivcrq62JPO7Qovpjk5Mjx32Kqzr73f0jTdYhDid7eyLBA==","signature_status":"signed_v1","signed_at":"2026-07-05T07:23:26.388943Z","signed_message":"canonical_sha256_bytes"},"source_id":"2305.16311","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:09e4a765e18029d9efb508076c8ed70a6f2d1534373431b4b6bf834f106338af","sha256:558c33ef3b3cbf0cc1dafea61d70072653511a829299f6cad95da0d4b4f04b90"],"state_sha256":"08302d8c0944af69f3efecd56f00e5b9a32992982d2f82d51673e84eef02bc93"}