{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2023:XVTZFUTOTGGY4WAIIX6JQ4EOWA","short_pith_number":"pith:XVTZFUTO","schema_version":"1.0","canonical_sha256":"bd6792d26e998d8e580845fc98708eb032ac38e50e69d47b9b637098b15045dd","source":{"kind":"arxiv","id":"2305.03980","version":1},"attestation_state":"computed","paper":{"title":"Towards Prompt-robust Face Privacy Protection via Adversarial Decoupling Augmentation Framework","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CR"],"primary_cat":"cs.CV","authors_text":"Ding Liang, Huafeng Shi, Ruijia Wu, Yichao Wu, Yuhang Wang, Zhipeng Yu","submitted_at":"2023-05-06T09:00:50Z","abstract_excerpt":"Denoising diffusion models have shown remarkable potential in various generation tasks. The open-source large-scale text-to-image model, Stable Diffusion, becomes prevalent as it can generate realistic artistic or facial images with personalization through fine-tuning on a limited number of new samples. However, this has raised privacy concerns as adversaries can acquire facial images online and fine-tune text-to-image models for malicious editing, leading to baseless scandals, defamation, and disruption to victims' lives. Prior research efforts have focused on deriving adversarial loss from c"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2305.03980","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2023-05-06T09:00:50Z","cross_cats_sorted":["cs.CR"],"title_canon_sha256":"63ef3e0056c0b90062ff764e97df7afcd89e891bbfe207e684c416a0676d1d3f","abstract_canon_sha256":"13a4284d87af8d63d5aac6fadba4f4df9df9c418ec16c77ec7d3c77485ee4c3d"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T06:07:43.296560Z","signature_b64":"+Vyny7V3vcWH5bHXo6vI/+6zTin3KG8av+tuLjD8yDxKssriQahAzydwMzL2gKTfM+ARa/2US9p3lrqzdNouCg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"bd6792d26e998d8e580845fc98708eb032ac38e50e69d47b9b637098b15045dd","last_reissued_at":"2026-07-05T06:07:43.296167Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T06:07:43.296167Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Towards Prompt-robust Face Privacy Protection via Adversarial Decoupling Augmentation Framework","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CR"],"primary_cat":"cs.CV","authors_text":"Ding Liang, Huafeng Shi, Ruijia Wu, Yichao Wu, Yuhang Wang, Zhipeng Yu","submitted_at":"2023-05-06T09:00:50Z","abstract_excerpt":"Denoising diffusion models have shown remarkable potential in various generation tasks. The open-source large-scale text-to-image model, Stable Diffusion, becomes prevalent as it can generate realistic artistic or facial images with personalization through fine-tuning on a limited number of new samples. However, this has raised privacy concerns as adversaries can acquire facial images online and fine-tune text-to-image models for malicious editing, leading to baseless scandals, defamation, and disruption to victims' lives. Prior research efforts have focused on deriving adversarial loss from c"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2305.03980","kind":"arxiv","version":1},"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/2305.03980/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"},"aliases":[{"alias_kind":"arxiv","alias_value":"2305.03980","created_at":"2026-07-05T06:07:43.296223+00:00"},{"alias_kind":"arxiv_version","alias_value":"2305.03980v1","created_at":"2026-07-05T06:07:43.296223+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2305.03980","created_at":"2026-07-05T06:07:43.296223+00:00"},{"alias_kind":"pith_short_12","alias_value":"XVTZFUTOTGGY","created_at":"2026-07-05T06:07:43.296223+00:00"},{"alias_kind":"pith_short_16","alias_value":"XVTZFUTOTGGY4WAI","created_at":"2026-07-05T06:07:43.296223+00:00"},{"alias_kind":"pith_short_8","alias_value":"XVTZFUTO","created_at":"2026-07-05T06:07:43.296223+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/XVTZFUTOTGGY4WAIIX6JQ4EOWA","json":"https://pith.science/pith/XVTZFUTOTGGY4WAIIX6JQ4EOWA.json","graph_json":"https://pith.science/api/pith-number/XVTZFUTOTGGY4WAIIX6JQ4EOWA/graph.json","events_json":"https://pith.science/api/pith-number/XVTZFUTOTGGY4WAIIX6JQ4EOWA/events.json","paper":"https://pith.science/paper/XVTZFUTO"},"agent_actions":{"view_html":"https://pith.science/pith/XVTZFUTOTGGY4WAIIX6JQ4EOWA","download_json":"https://pith.science/pith/XVTZFUTOTGGY4WAIIX6JQ4EOWA.json","view_paper":"https://pith.science/paper/XVTZFUTO","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2305.03980&json=true","fetch_graph":"https://pith.science/api/pith-number/XVTZFUTOTGGY4WAIIX6JQ4EOWA/graph.json","fetch_events":"https://pith.science/api/pith-number/XVTZFUTOTGGY4WAIIX6JQ4EOWA/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/XVTZFUTOTGGY4WAIIX6JQ4EOWA/action/timestamp_anchor","attest_storage":"https://pith.science/pith/XVTZFUTOTGGY4WAIIX6JQ4EOWA/action/storage_attestation","attest_author":"https://pith.science/pith/XVTZFUTOTGGY4WAIIX6JQ4EOWA/action/author_attestation","sign_citation":"https://pith.science/pith/XVTZFUTOTGGY4WAIIX6JQ4EOWA/action/citation_signature","submit_replication":"https://pith.science/pith/XVTZFUTOTGGY4WAIIX6JQ4EOWA/action/replication_record"}},"created_at":"2026-07-05T06:07:43.296223+00:00","updated_at":"2026-07-05T06:07:43.296223+00:00"}