{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:6YUI4ZSQBDPSTQ37NISIJNHD6M","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":"8b09a484496828cd1ab12d85e4b45178ec99ee790ebba95a83b728494d49741c","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CV","submitted_at":"2023-05-23T01:14:53Z","title_canon_sha256":"489b1ad6f73b191de697a04b7dff46c903f648898234bcc873e0d658f4e732c8"},"schema_version":"1.0","source":{"id":"2305.13579","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2305.13579","created_at":"2026-07-05T06:12:54Z"},{"alias_kind":"arxiv_version","alias_value":"2305.13579v1","created_at":"2026-07-05T06:12:54Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2305.13579","created_at":"2026-07-05T06:12:54Z"},{"alias_kind":"pith_short_12","alias_value":"6YUI4ZSQBDPS","created_at":"2026-07-05T06:12:54Z"},{"alias_kind":"pith_short_16","alias_value":"6YUI4ZSQBDPSTQ37","created_at":"2026-07-05T06:12:54Z"},{"alias_kind":"pith_short_8","alias_value":"6YUI4ZSQ","created_at":"2026-07-05T06:12:54Z"}],"graph_snapshots":[{"event_id":"sha256:aad860e1a39fbdd40358e04698e8a91f79b4c0104b39b8a8b029e7f2978ee3d5","target":"graph","created_at":"2026-07-05T06:12:54Z","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/2305.13579/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Recent text-to-image generation models have demonstrated impressive capability of generating text-aligned images with high fidelity. However, generating images of novel concept provided by the user input image is still a challenging task. To address this problem, researchers have been exploring various methods for customizing pre-trained text-to-image generation models. Currently, most existing methods for customizing pre-trained text-to-image generation models involve the use of regularization techniques to prevent over-fitting. While regularization will ease the challenge of customization an","authors_text":"Jinhui Xu, Ruiyi Zhang, Tong Sun, Yufan Zhou","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CV","submitted_at":"2023-05-23T01:14:53Z","title":"Enhancing Detail Preservation for Customized Text-to-Image Generation: A Regularization-Free Approach"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2305.13579","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:a3d3c95bc17e84fb7c428cd5a8f1ce3631d3a6c93fb7de1f943fa84307819dfc","target":"record","created_at":"2026-07-05T06:12:54Z","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":"8b09a484496828cd1ab12d85e4b45178ec99ee790ebba95a83b728494d49741c","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CV","submitted_at":"2023-05-23T01:14:53Z","title_canon_sha256":"489b1ad6f73b191de697a04b7dff46c903f648898234bcc873e0d658f4e732c8"},"schema_version":"1.0","source":{"id":"2305.13579","kind":"arxiv","version":1}},"canonical_sha256":"f6288e665008df29c37f6a2484b4e3f31359b38894daad6258a9fe17cfcc2683","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"f6288e665008df29c37f6a2484b4e3f31359b38894daad6258a9fe17cfcc2683","first_computed_at":"2026-07-05T06:12:54.566650Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T06:12:54.566650Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"rBTZJCT63VgDeZpa/i0tgvt613YaDqdXZZzZvRUetXhjse4vSZ2+muzp3s9ERE+a/9d9AqEWI4cb+elldkHQAw==","signature_status":"signed_v1","signed_at":"2026-07-05T06:12:54.567045Z","signed_message":"canonical_sha256_bytes"},"source_id":"2305.13579","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:a3d3c95bc17e84fb7c428cd5a8f1ce3631d3a6c93fb7de1f943fa84307819dfc","sha256:aad860e1a39fbdd40358e04698e8a91f79b4c0104b39b8a8b029e7f2978ee3d5"],"state_sha256":"c03dce28a1227fbb2ccca9644516e94cbcf6ed4913a4e9060d4505c2d51647e7"}