{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2023:UDOVMWSYP73FQDK3I6G4BYHF5M","short_pith_number":"pith:UDOVMWSY","schema_version":"1.0","canonical_sha256":"a0dd565a587ff6580d5b478dc0e0e5eb3233ebc4852ded85cc302755baff47a6","source":{"kind":"arxiv","id":"2306.04642","version":4},"attestation_state":"computed","paper":{"title":"DiffusionShield: A Watermark for Copyright Protection against Generative Diffusion Models","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.CV","cs.LG"],"primary_cat":"cs.CR","authors_text":"Han Xu, Hui Liu, Jie Ren, Jiliang Tang, Lichao Sun, Pengfei He, Yingqian Cui, Yue Xing","submitted_at":"2023-05-25T11:59:28Z","abstract_excerpt":"Recently, Generative Diffusion Models (GDMs) have showcased their remarkable capabilities in learning and generating images. A large community of GDMs has naturally emerged, further promoting the diversified applications of GDMs in various fields. However, this unrestricted proliferation has raised serious concerns about copyright protection. For example, artists including painters and photographers are becoming increasingly concerned that GDMs could effortlessly replicate their unique creative works without authorization. In response to these challenges, we introduce a novel watermarking sche"},"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":"2306.04642","kind":"arxiv","version":4},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CR","submitted_at":"2023-05-25T11:59:28Z","cross_cats_sorted":["cs.CV","cs.LG"],"title_canon_sha256":"bcd77777a0868b5182386d18f6d32aaa5700fa80790569e6ded4e4222e6dfd42","abstract_canon_sha256":"9c0b8450f1eae8d45ce5fc9edfff39e1c3f5e41defff0fbf4cd0dc83664295d6"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T08:17:27.642400Z","signature_b64":"xJjY8fmYi4nYQhl4+niS+UV9h/1G8dLOG6uKtKiw5XrLJRLvxN0MXiVGxMoc9nVCGfWDIrqZPBISjgcLMMQGDg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"a0dd565a587ff6580d5b478dc0e0e5eb3233ebc4852ded85cc302755baff47a6","last_reissued_at":"2026-07-05T08:17:27.641909Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T08:17:27.641909Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"DiffusionShield: A Watermark for Copyright Protection against Generative Diffusion Models","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.CV","cs.LG"],"primary_cat":"cs.CR","authors_text":"Han Xu, Hui Liu, Jie Ren, Jiliang Tang, Lichao Sun, Pengfei He, Yingqian Cui, Yue Xing","submitted_at":"2023-05-25T11:59:28Z","abstract_excerpt":"Recently, Generative Diffusion Models (GDMs) have showcased their remarkable capabilities in learning and generating images. A large community of GDMs has naturally emerged, further promoting the diversified applications of GDMs in various fields. However, this unrestricted proliferation has raised serious concerns about copyright protection. For example, artists including painters and photographers are becoming increasingly concerned that GDMs could effortlessly replicate their unique creative works without authorization. In response to these challenges, we introduce a novel watermarking sche"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2306.04642","kind":"arxiv","version":4},"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/2306.04642/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":"2306.04642","created_at":"2026-07-05T08:17:27.641971+00:00"},{"alias_kind":"arxiv_version","alias_value":"2306.04642v4","created_at":"2026-07-05T08:17:27.641971+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2306.04642","created_at":"2026-07-05T08:17:27.641971+00:00"},{"alias_kind":"pith_short_12","alias_value":"UDOVMWSYP73F","created_at":"2026-07-05T08:17:27.641971+00:00"},{"alias_kind":"pith_short_16","alias_value":"UDOVMWSYP73FQDK3","created_at":"2026-07-05T08:17:27.641971+00:00"},{"alias_kind":"pith_short_8","alias_value":"UDOVMWSY","created_at":"2026-07-05T08:17:27.641971+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":3,"internal_anchor_count":0,"sample":[{"citing_arxiv_id":"2512.10248","citing_title":"RobustSora: De-Watermarked Benchmark for Robust AI-Generated Video Detection","ref_index":2,"is_internal_anchor":false},{"citing_arxiv_id":"2604.16363","citing_title":"CSF: Black-box Fingerprinting via Compositional Semantics for Text-to-Image Models","ref_index":6,"is_internal_anchor":false},{"citing_arxiv_id":"2605.09005","citing_title":"Towards Backdoor-Based Ownership Verification for Vision-Language-Action Models","ref_index":6,"is_internal_anchor":false}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/UDOVMWSYP73FQDK3I6G4BYHF5M","json":"https://pith.science/pith/UDOVMWSYP73FQDK3I6G4BYHF5M.json","graph_json":"https://pith.science/api/pith-number/UDOVMWSYP73FQDK3I6G4BYHF5M/graph.json","events_json":"https://pith.science/api/pith-number/UDOVMWSYP73FQDK3I6G4BYHF5M/events.json","paper":"https://pith.science/paper/UDOVMWSY"},"agent_actions":{"view_html":"https://pith.science/pith/UDOVMWSYP73FQDK3I6G4BYHF5M","download_json":"https://pith.science/pith/UDOVMWSYP73FQDK3I6G4BYHF5M.json","view_paper":"https://pith.science/paper/UDOVMWSY","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2306.04642&json=true","fetch_graph":"https://pith.science/api/pith-number/UDOVMWSYP73FQDK3I6G4BYHF5M/graph.json","fetch_events":"https://pith.science/api/pith-number/UDOVMWSYP73FQDK3I6G4BYHF5M/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/UDOVMWSYP73FQDK3I6G4BYHF5M/action/timestamp_anchor","attest_storage":"https://pith.science/pith/UDOVMWSYP73FQDK3I6G4BYHF5M/action/storage_attestation","attest_author":"https://pith.science/pith/UDOVMWSYP73FQDK3I6G4BYHF5M/action/author_attestation","sign_citation":"https://pith.science/pith/UDOVMWSYP73FQDK3I6G4BYHF5M/action/citation_signature","submit_replication":"https://pith.science/pith/UDOVMWSYP73FQDK3I6G4BYHF5M/action/replication_record"}},"created_at":"2026-07-05T08:17:27.641971+00:00","updated_at":"2026-07-05T08:17:27.641971+00:00"}