{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:DGNTJXOARG3Q3WREEGCOBPCMZT","short_pith_number":"pith:DGNTJXOA","canonical_record":{"source":{"id":"2311.14631","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2023-11-24T17:55:10Z","cross_cats_sorted":[],"title_canon_sha256":"e55a5a41b74b634d600b8f9aa6a4538096076fd4c0c5e06cb3177c0c9c889f0d","abstract_canon_sha256":"99a1fbb443f9565fb62effc9cfdd3287d9f064d2195e5e51749874f6b4cc3029"},"schema_version":"1.0"},"canonical_sha256":"199b34ddc089b70dda242184e0bc4cccfda967f8c82a0aa078d16cec11d3caa0","source":{"kind":"arxiv","id":"2311.14631","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2311.14631","created_at":"2026-07-05T07:18:32Z"},{"alias_kind":"arxiv_version","alias_value":"2311.14631v2","created_at":"2026-07-05T07:18:32Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2311.14631","created_at":"2026-07-05T07:18:32Z"},{"alias_kind":"pith_short_12","alias_value":"DGNTJXOARG3Q","created_at":"2026-07-05T07:18:32Z"},{"alias_kind":"pith_short_16","alias_value":"DGNTJXOARG3Q3WRE","created_at":"2026-07-05T07:18:32Z"},{"alias_kind":"pith_short_8","alias_value":"DGNTJXOA","created_at":"2026-07-05T07:18:32Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:DGNTJXOARG3Q3WREEGCOBPCMZT","target":"record","payload":{"canonical_record":{"source":{"id":"2311.14631","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2023-11-24T17:55:10Z","cross_cats_sorted":[],"title_canon_sha256":"e55a5a41b74b634d600b8f9aa6a4538096076fd4c0c5e06cb3177c0c9c889f0d","abstract_canon_sha256":"99a1fbb443f9565fb62effc9cfdd3287d9f064d2195e5e51749874f6b4cc3029"},"schema_version":"1.0"},"canonical_sha256":"199b34ddc089b70dda242184e0bc4cccfda967f8c82a0aa078d16cec11d3caa0","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T07:18:32.478927Z","signature_b64":"mQSGB7ORGNzzQiTcm1r9ql8FeaX58pyJt5q41hQ+jTJ5ascBiPSHEy0pZsiteoa/6/VIaD7zMdoOAv0dwxNBCg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"199b34ddc089b70dda242184e0bc4cccfda967f8c82a0aa078d16cec11d3caa0","last_reissued_at":"2026-07-05T07:18:32.478383Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T07:18:32.478383Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2311.14631","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T07:18:32Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"XH4h1HUXTJ+DMJoRQtpT4FONZ2pBDsVemEhxadlUAFqyCMmVqQwvQ3W8dK3tjzd3SyHSIOwUQMdeOaO5IDfeBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-13T21:43:04.646284Z"},"content_sha256":"86fad7613ebb8a8abfdfafcab5ab2e4ba31c6af88bd86f2d6144412a79d07c02","schema_version":"1.0","event_id":"sha256:86fad7613ebb8a8abfdfafcab5ab2e4ba31c6af88bd86f2d6144412a79d07c02"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:DGNTJXOARG3Q3WREEGCOBPCMZT","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"CatVersion: Concatenating Embeddings for Diffusion-Based Text-to-Image Personalization","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Mingrui Zhu, Nannan Wang, Ruoyu Zhao, Shiyin Dong, Xinbo Gao","submitted_at":"2023-11-24T17:55:10Z","abstract_excerpt":"We propose CatVersion, an inversion-based method that learns the personalized concept through a handful of examples. Subsequently, users can utilize text prompts to generate images that embody the personalized concept, thereby achieving text-to-image personalization. In contrast to existing approaches that emphasize word embedding learning or parameter fine-tuning for the diffusion model, which potentially causes concept dilution or overfitting, our method concatenates embeddings on the feature-dense space of the text encoder in the diffusion model to learn the gap between the personalized con"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2311.14631","kind":"arxiv","version":2},"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/2311.14631/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":"2026-07-05T07:18:32Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"xCvhHlEHaQc3kHeHvJjE51o02kpA3K0DpNsgD+hV1EqliKsS15n9UVkkOV2ujLWtCtSVVJlCuQfeWrt4X8GhBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-13T21:43:04.646742Z"},"content_sha256":"3cc90c399840d90636266fa62f1ce85fa6283db76fc60ac5598beaa5a399ab74","schema_version":"1.0","event_id":"sha256:3cc90c399840d90636266fa62f1ce85fa6283db76fc60ac5598beaa5a399ab74"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/DGNTJXOARG3Q3WREEGCOBPCMZT/bundle.json","state_url":"https://pith.science/pith/DGNTJXOARG3Q3WREEGCOBPCMZT/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/DGNTJXOARG3Q3WREEGCOBPCMZT/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":"2026-08-13T21:43:04Z","links":{"resolver":"https://pith.science/pith/DGNTJXOARG3Q3WREEGCOBPCMZT","bundle":"https://pith.science/pith/DGNTJXOARG3Q3WREEGCOBPCMZT/bundle.json","state":"https://pith.science/pith/DGNTJXOARG3Q3WREEGCOBPCMZT/state.json","well_known_bundle":"https://pith.science/.well-known/pith/DGNTJXOARG3Q3WREEGCOBPCMZT/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:DGNTJXOARG3Q3WREEGCOBPCMZT","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":"99a1fbb443f9565fb62effc9cfdd3287d9f064d2195e5e51749874f6b4cc3029","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2023-11-24T17:55:10Z","title_canon_sha256":"e55a5a41b74b634d600b8f9aa6a4538096076fd4c0c5e06cb3177c0c9c889f0d"},"schema_version":"1.0","source":{"id":"2311.14631","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2311.14631","created_at":"2026-07-05T07:18:32Z"},{"alias_kind":"arxiv_version","alias_value":"2311.14631v2","created_at":"2026-07-05T07:18:32Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2311.14631","created_at":"2026-07-05T07:18:32Z"},{"alias_kind":"pith_short_12","alias_value":"DGNTJXOARG3Q","created_at":"2026-07-05T07:18:32Z"},{"alias_kind":"pith_short_16","alias_value":"DGNTJXOARG3Q3WRE","created_at":"2026-07-05T07:18:32Z"},{"alias_kind":"pith_short_8","alias_value":"DGNTJXOA","created_at":"2026-07-05T07:18:32Z"}],"graph_snapshots":[{"event_id":"sha256:3cc90c399840d90636266fa62f1ce85fa6283db76fc60ac5598beaa5a399ab74","target":"graph","created_at":"2026-07-05T07:18:32Z","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/2311.14631/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"We propose CatVersion, an inversion-based method that learns the personalized concept through a handful of examples. Subsequently, users can utilize text prompts to generate images that embody the personalized concept, thereby achieving text-to-image personalization. In contrast to existing approaches that emphasize word embedding learning or parameter fine-tuning for the diffusion model, which potentially causes concept dilution or overfitting, our method concatenates embeddings on the feature-dense space of the text encoder in the diffusion model to learn the gap between the personalized con","authors_text":"Mingrui Zhu, Nannan Wang, Ruoyu Zhao, Shiyin Dong, Xinbo Gao","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2023-11-24T17:55:10Z","title":"CatVersion: Concatenating Embeddings for Diffusion-Based Text-to-Image Personalization"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2311.14631","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":"sha256:86fad7613ebb8a8abfdfafcab5ab2e4ba31c6af88bd86f2d6144412a79d07c02","target":"record","created_at":"2026-07-05T07:18:32Z","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":"99a1fbb443f9565fb62effc9cfdd3287d9f064d2195e5e51749874f6b4cc3029","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2023-11-24T17:55:10Z","title_canon_sha256":"e55a5a41b74b634d600b8f9aa6a4538096076fd4c0c5e06cb3177c0c9c889f0d"},"schema_version":"1.0","source":{"id":"2311.14631","kind":"arxiv","version":2}},"canonical_sha256":"199b34ddc089b70dda242184e0bc4cccfda967f8c82a0aa078d16cec11d3caa0","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"199b34ddc089b70dda242184e0bc4cccfda967f8c82a0aa078d16cec11d3caa0","first_computed_at":"2026-07-05T07:18:32.478383Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T07:18:32.478383Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"mQSGB7ORGNzzQiTcm1r9ql8FeaX58pyJt5q41hQ+jTJ5ascBiPSHEy0pZsiteoa/6/VIaD7zMdoOAv0dwxNBCg==","signature_status":"signed_v1","signed_at":"2026-07-05T07:18:32.478927Z","signed_message":"canonical_sha256_bytes"},"source_id":"2311.14631","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:86fad7613ebb8a8abfdfafcab5ab2e4ba31c6af88bd86f2d6144412a79d07c02","sha256:3cc90c399840d90636266fa62f1ce85fa6283db76fc60ac5598beaa5a399ab74"],"state_sha256":"348a80fe3a2c1d98f48424a22633a9156ccf953287d145b5d6d718cd9773afee"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"hN2QsOkhZS/3XpMXyD9ibSDBqZ6zsWDt5tt2s0xV3DOzher0j2EakYLRAIcg2a4+I1aXHLp7gVh3vxyMby0FAQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-13T21:43:04.659548Z","bundle_sha256":"0e62f96e7d70601e3eebdea61a1408a5ea1aef8aea31ce09fee0ecc5d5e82405"}}