{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2023:WDPHWDLP3RRI5IY23QW6UVZWVX","short_pith_number":"pith:WDPHWDLP","schema_version":"1.0","canonical_sha256":"b0de7b0d6fdc628ea31adc2dea5736adfaab18099482c9d9307bebe7a26f754d","source":{"kind":"arxiv","id":"2311.04584","version":2},"attestation_state":"computed","paper":{"title":"Weakly-supervised deepfake localization in diffusion-generated images","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Dan Oneata, Dragos Tantaru, Elisabeta Oneata","submitted_at":"2023-11-08T10:27:36Z","abstract_excerpt":"The remarkable generative capabilities of denoising diffusion models have raised new concerns regarding the authenticity of the images we see every day on the Internet. However, the vast majority of existing deepfake detection models are tested against previous generative approaches (e.g. GAN) and usually provide only a \"fake\" or \"real\" label per image. We believe a more informative output would be to augment the per-image label with a localization map indicating which regions of the input have been manipulated. To this end, we frame this task as a weakly-supervised localization problem and id"},"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":"2311.04584","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CV","submitted_at":"2023-11-08T10:27:36Z","cross_cats_sorted":[],"title_canon_sha256":"c8ca1c4447e0c09a1e6f0ef9a0a110579eebaae7eb1e4190ef31ec730c66499e","abstract_canon_sha256":"9d231ed2d4dbcbbf822ea7445d7dc0fe3329d6705c8d76305d5e1ac51e1ef121"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T07:12:01.466158Z","signature_b64":"+h6VVNvsuCaVfzv6T5rxsqaBerOfG4F/AZXHAKGsnq4NDuPMuzL/3qvF8PshiAgxSvHRzcKEAJei0nExOKDWAw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"b0de7b0d6fdc628ea31adc2dea5736adfaab18099482c9d9307bebe7a26f754d","last_reissued_at":"2026-07-05T07:12:01.465693Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T07:12:01.465693Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Weakly-supervised deepfake localization in diffusion-generated images","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Dan Oneata, Dragos Tantaru, Elisabeta Oneata","submitted_at":"2023-11-08T10:27:36Z","abstract_excerpt":"The remarkable generative capabilities of denoising diffusion models have raised new concerns regarding the authenticity of the images we see every day on the Internet. However, the vast majority of existing deepfake detection models are tested against previous generative approaches (e.g. GAN) and usually provide only a \"fake\" or \"real\" label per image. We believe a more informative output would be to augment the per-image label with a localization map indicating which regions of the input have been manipulated. To this end, we frame this task as a weakly-supervised localization problem and id"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2311.04584","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/2311.04584/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":"2311.04584","created_at":"2026-07-05T07:12:01.465751+00:00"},{"alias_kind":"arxiv_version","alias_value":"2311.04584v2","created_at":"2026-07-05T07:12:01.465751+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2311.04584","created_at":"2026-07-05T07:12:01.465751+00:00"},{"alias_kind":"pith_short_12","alias_value":"WDPHWDLP3RRI","created_at":"2026-07-05T07:12:01.465751+00:00"},{"alias_kind":"pith_short_16","alias_value":"WDPHWDLP3RRI5IY2","created_at":"2026-07-05T07:12:01.465751+00:00"},{"alias_kind":"pith_short_8","alias_value":"WDPHWDLP","created_at":"2026-07-05T07:12:01.465751+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/WDPHWDLP3RRI5IY23QW6UVZWVX","json":"https://pith.science/pith/WDPHWDLP3RRI5IY23QW6UVZWVX.json","graph_json":"https://pith.science/api/pith-number/WDPHWDLP3RRI5IY23QW6UVZWVX/graph.json","events_json":"https://pith.science/api/pith-number/WDPHWDLP3RRI5IY23QW6UVZWVX/events.json","paper":"https://pith.science/paper/WDPHWDLP"},"agent_actions":{"view_html":"https://pith.science/pith/WDPHWDLP3RRI5IY23QW6UVZWVX","download_json":"https://pith.science/pith/WDPHWDLP3RRI5IY23QW6UVZWVX.json","view_paper":"https://pith.science/paper/WDPHWDLP","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2311.04584&json=true","fetch_graph":"https://pith.science/api/pith-number/WDPHWDLP3RRI5IY23QW6UVZWVX/graph.json","fetch_events":"https://pith.science/api/pith-number/WDPHWDLP3RRI5IY23QW6UVZWVX/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/WDPHWDLP3RRI5IY23QW6UVZWVX/action/timestamp_anchor","attest_storage":"https://pith.science/pith/WDPHWDLP3RRI5IY23QW6UVZWVX/action/storage_attestation","attest_author":"https://pith.science/pith/WDPHWDLP3RRI5IY23QW6UVZWVX/action/author_attestation","sign_citation":"https://pith.science/pith/WDPHWDLP3RRI5IY23QW6UVZWVX/action/citation_signature","submit_replication":"https://pith.science/pith/WDPHWDLP3RRI5IY23QW6UVZWVX/action/replication_record"}},"created_at":"2026-07-05T07:12:01.465751+00:00","updated_at":"2026-07-05T07:12:01.465751+00:00"}