{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:6C7FLKNL3AYA7R34P3ENBAAQR4","short_pith_number":"pith:6C7FLKNL","canonical_record":{"source":{"id":"2403.06803","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-03-11T15:22:28Z","cross_cats_sorted":[],"title_canon_sha256":"49907da5c8cab9a69b6c762eea9c8dad60bb02652830dc27b3292232f625ba63","abstract_canon_sha256":"cf0cc26a2413be69eca502ec6081f9f80bde0e4a53de39f291ae8c22c436b08b"},"schema_version":"1.0"},"canonical_sha256":"f0be55a9abd8300fc77c7ec8d080108f2720e20b81a891735f5e9d80ea253b63","source":{"kind":"arxiv","id":"2403.06803","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2403.06803","created_at":"2026-07-05T07:54:42Z"},{"alias_kind":"arxiv_version","alias_value":"2403.06803v1","created_at":"2026-07-05T07:54:42Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2403.06803","created_at":"2026-07-05T07:54:42Z"},{"alias_kind":"pith_short_12","alias_value":"6C7FLKNL3AYA","created_at":"2026-07-05T07:54:42Z"},{"alias_kind":"pith_short_16","alias_value":"6C7FLKNL3AYA7R34","created_at":"2026-07-05T07:54:42Z"},{"alias_kind":"pith_short_8","alias_value":"6C7FLKNL","created_at":"2026-07-05T07:54:42Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:6C7FLKNL3AYA7R34P3ENBAAQR4","target":"record","payload":{"canonical_record":{"source":{"id":"2403.06803","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-03-11T15:22:28Z","cross_cats_sorted":[],"title_canon_sha256":"49907da5c8cab9a69b6c762eea9c8dad60bb02652830dc27b3292232f625ba63","abstract_canon_sha256":"cf0cc26a2413be69eca502ec6081f9f80bde0e4a53de39f291ae8c22c436b08b"},"schema_version":"1.0"},"canonical_sha256":"f0be55a9abd8300fc77c7ec8d080108f2720e20b81a891735f5e9d80ea253b63","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T07:54:42.978915Z","signature_b64":"9s68L9EI4PrQJO5PUDXyKZpk6G+KAJt/5AhHUQgXZghyHYK/aFl0jVR/FBpxC0gnE8ncM/+HP8xH4EBkAKBiAA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"f0be55a9abd8300fc77c7ec8d080108f2720e20b81a891735f5e9d80ea253b63","last_reissued_at":"2026-07-05T07:54:42.978428Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T07:54:42.978428Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2403.06803","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T07:54:42Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"2oYHHsAUZJZmMfUNf2vuHdveGuyJYugaN5v78aRcpwfuIXN3dDr18MHFNIj3B4aftdYPUMwZZWVn3cNdbIJhDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-31T13:27:24.659274Z"},"content_sha256":"f4623bb0ce76aad2b4bd8b677fa9ed43e717f6a217807841dd99bb6a0295c78f","schema_version":"1.0","event_id":"sha256:f4623bb0ce76aad2b4bd8b677fa9ed43e717f6a217807841dd99bb6a0295c78f"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:6C7FLKNL3AYA7R34P3ENBAAQR4","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Data-Independent Operator: A Training-Free Artifact Representation Extractor for Generalizable Deepfake Detection","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Baoyuan Wu, Chuangchuang Tan, Huan Liu, Ping Liu, Renshuai Tao, Yao Zhao, Yunchao Wei","submitted_at":"2024-03-11T15:22:28Z","abstract_excerpt":"Recently, the proliferation of increasingly realistic synthetic images generated by various generative adversarial networks has increased the risk of misuse. Consequently, there is a pressing need to develop a generalizable detector for accurately recognizing fake images. The conventional methods rely on generating diverse training sources or large pretrained models. In this work, we show that, on the contrary, the small and training-free filter is sufficient to capture more general artifact representations. Due to its unbias towards both the training and test sources, we define it as Data-Ind"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2403.06803","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/2403.06803/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":"2026-07-05T07:54:42Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"zleefwt/aFW6/IMaZSCnbf456Ue7M6COeLqIxgXRH0fm+BSWz5BnBmaCYYROKwbrFI9OSvoug3MJDfXchkuMDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-31T13:27:24.659576Z"},"content_sha256":"fc4e5885f96a55eadf7e8186eeb97ea1319a62fce9fde68fa33550391f341d24","schema_version":"1.0","event_id":"sha256:fc4e5885f96a55eadf7e8186eeb97ea1319a62fce9fde68fa33550391f341d24"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/6C7FLKNL3AYA7R34P3ENBAAQR4/bundle.json","state_url":"https://pith.science/pith/6C7FLKNL3AYA7R34P3ENBAAQR4/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/6C7FLKNL3AYA7R34P3ENBAAQR4/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":"2026-07-31T13:27:24Z","links":{"resolver":"https://pith.science/pith/6C7FLKNL3AYA7R34P3ENBAAQR4","bundle":"https://pith.science/pith/6C7FLKNL3AYA7R34P3ENBAAQR4/bundle.json","state":"https://pith.science/pith/6C7FLKNL3AYA7R34P3ENBAAQR4/state.json","well_known_bundle":"https://pith.science/.well-known/pith/6C7FLKNL3AYA7R34P3ENBAAQR4/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:6C7FLKNL3AYA7R34P3ENBAAQR4","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":"cf0cc26a2413be69eca502ec6081f9f80bde0e4a53de39f291ae8c22c436b08b","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-03-11T15:22:28Z","title_canon_sha256":"49907da5c8cab9a69b6c762eea9c8dad60bb02652830dc27b3292232f625ba63"},"schema_version":"1.0","source":{"id":"2403.06803","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2403.06803","created_at":"2026-07-05T07:54:42Z"},{"alias_kind":"arxiv_version","alias_value":"2403.06803v1","created_at":"2026-07-05T07:54:42Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2403.06803","created_at":"2026-07-05T07:54:42Z"},{"alias_kind":"pith_short_12","alias_value":"6C7FLKNL3AYA","created_at":"2026-07-05T07:54:42Z"},{"alias_kind":"pith_short_16","alias_value":"6C7FLKNL3AYA7R34","created_at":"2026-07-05T07:54:42Z"},{"alias_kind":"pith_short_8","alias_value":"6C7FLKNL","created_at":"2026-07-05T07:54:42Z"}],"graph_snapshots":[{"event_id":"sha256:fc4e5885f96a55eadf7e8186eeb97ea1319a62fce9fde68fa33550391f341d24","target":"graph","created_at":"2026-07-05T07:54:42Z","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/2403.06803/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Recently, the proliferation of increasingly realistic synthetic images generated by various generative adversarial networks has increased the risk of misuse. Consequently, there is a pressing need to develop a generalizable detector for accurately recognizing fake images. The conventional methods rely on generating diverse training sources or large pretrained models. In this work, we show that, on the contrary, the small and training-free filter is sufficient to capture more general artifact representations. Due to its unbias towards both the training and test sources, we define it as Data-Ind","authors_text":"Baoyuan Wu, Chuangchuang Tan, Huan Liu, Ping Liu, Renshuai Tao, Yao Zhao, Yunchao Wei","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-03-11T15:22:28Z","title":"Data-Independent Operator: A Training-Free Artifact Representation Extractor for Generalizable Deepfake Detection"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2403.06803","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:f4623bb0ce76aad2b4bd8b677fa9ed43e717f6a217807841dd99bb6a0295c78f","target":"record","created_at":"2026-07-05T07:54:42Z","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":"cf0cc26a2413be69eca502ec6081f9f80bde0e4a53de39f291ae8c22c436b08b","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-03-11T15:22:28Z","title_canon_sha256":"49907da5c8cab9a69b6c762eea9c8dad60bb02652830dc27b3292232f625ba63"},"schema_version":"1.0","source":{"id":"2403.06803","kind":"arxiv","version":1}},"canonical_sha256":"f0be55a9abd8300fc77c7ec8d080108f2720e20b81a891735f5e9d80ea253b63","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"f0be55a9abd8300fc77c7ec8d080108f2720e20b81a891735f5e9d80ea253b63","first_computed_at":"2026-07-05T07:54:42.978428Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T07:54:42.978428Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"9s68L9EI4PrQJO5PUDXyKZpk6G+KAJt/5AhHUQgXZghyHYK/aFl0jVR/FBpxC0gnE8ncM/+HP8xH4EBkAKBiAA==","signature_status":"signed_v1","signed_at":"2026-07-05T07:54:42.978915Z","signed_message":"canonical_sha256_bytes"},"source_id":"2403.06803","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:f4623bb0ce76aad2b4bd8b677fa9ed43e717f6a217807841dd99bb6a0295c78f","sha256:fc4e5885f96a55eadf7e8186eeb97ea1319a62fce9fde68fa33550391f341d24"],"state_sha256":"bbb84127d077b830b779a81a4f2bd938082fb6b3a9d236c70c114f71c6bed9bf"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"H8uFZ8TXv76T+KaV/hZ7rZRBu44zYkWMenHHUT4un+M+8yo2G7yzaFigJCc5eM7DFg1BfYwOjJ5Pge2pXp2/AQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-31T13:27:24.661798Z","bundle_sha256":"eaa30e4dca083cb96e62fd829f61cc337575162fa101cc5a4579c4ed3cbe53aa"}}