{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:AIETJQIY26BJ4EOFQMYDWPJ25A","short_pith_number":"pith:AIETJQIY","canonical_record":{"source":{"id":"2304.06408","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2023-04-13T11:13:19Z","cross_cats_sorted":[],"title_canon_sha256":"fe7710d572fddc55d15bfb8f89b3986d7a180bee0766ce24f3be3d691caea831","abstract_canon_sha256":"5b92e6370124c703a504439274dfcfa998ee51c24d00c119ec781af58633b784"},"schema_version":"1.0"},"canonical_sha256":"020934c118d7829e11c583303b3d3ae8018cd8de2a62e11b7fa0b119744896b5","source":{"kind":"arxiv","id":"2304.06408","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2304.06408","created_at":"2026-07-05T06:26:01Z"},{"alias_kind":"arxiv_version","alias_value":"2304.06408v2","created_at":"2026-07-05T06:26:01Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2304.06408","created_at":"2026-07-05T06:26:01Z"},{"alias_kind":"pith_short_12","alias_value":"AIETJQIY26BJ","created_at":"2026-07-05T06:26:01Z"},{"alias_kind":"pith_short_16","alias_value":"AIETJQIY26BJ4EOF","created_at":"2026-07-05T06:26:01Z"},{"alias_kind":"pith_short_8","alias_value":"AIETJQIY","created_at":"2026-07-05T06:26:01Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:AIETJQIY26BJ4EOFQMYDWPJ25A","target":"record","payload":{"canonical_record":{"source":{"id":"2304.06408","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2023-04-13T11:13:19Z","cross_cats_sorted":[],"title_canon_sha256":"fe7710d572fddc55d15bfb8f89b3986d7a180bee0766ce24f3be3d691caea831","abstract_canon_sha256":"5b92e6370124c703a504439274dfcfa998ee51c24d00c119ec781af58633b784"},"schema_version":"1.0"},"canonical_sha256":"020934c118d7829e11c583303b3d3ae8018cd8de2a62e11b7fa0b119744896b5","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T06:26:01.586009Z","signature_b64":"K2pxJtEd5tpODSeQz7Wk3mgjz+ifwJ/u1svIRizshQCBK37gbE3tEeZpdjaknuZx+PZ5VMxzGdntFhd16wR2DA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"020934c118d7829e11c583303b3d3ae8018cd8de2a62e11b7fa0b119744896b5","last_reissued_at":"2026-07-05T06:26:01.585520Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T06:26:01.585520Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2304.06408","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T06:26:01Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"w62U4EWr3MGk2+KY9Tem8ov3Y6msjHr4IuGftghfxfebjJu9pBK5B6C4+qu0IIquyGkw7Gg2+ItE/2g2FVgYCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-10T02:46:07.084928Z"},"content_sha256":"d672fec8dc7e37915a9bbf882effd252ab3f349656b6c3cc706d0a25865855ec","schema_version":"1.0","event_id":"sha256:d672fec8dc7e37915a9bbf882effd252ab3f349656b6c3cc706d0a25865855ec"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:AIETJQIY26BJ4EOFQMYDWPJ25A","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Intriguing properties of synthetic images: from generative adversarial networks to diffusion models","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Davide Cozzolino, Giovanni Poggi, Koki Nagano, Luisa Verdoliva, Riccardo Corvi","submitted_at":"2023-04-13T11:13:19Z","abstract_excerpt":"Detecting fake images is becoming a major goal of computer vision. This need is becoming more and more pressing with the continuous improvement of synthesis methods based on Generative Adversarial Networks (GAN), and even more with the appearance of powerful methods based on Diffusion Models (DM). Towards this end, it is important to gain insight into which image features better discriminate fake images from real ones. In this paper we report on our systematic study of a large number of image generators of different families, aimed at discovering the most forensically relevant characteristics "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2304.06408","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/2304.06408/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":"2026-07-05T06:26:01Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"e00x4AvbA7liDuP7r9JpyvKLGTm4+jL3oR7CgqF5Q1efm76V0ECN46lBSQ3NlUffOeWwXB1XDv87d5uHpNvnCw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-10T02:46:07.085560Z"},"content_sha256":"421d4cd02fce5cf0d6bb473057d394b9b8b12493a75c8ed11b9ffccc41f3dd4d","schema_version":"1.0","event_id":"sha256:421d4cd02fce5cf0d6bb473057d394b9b8b12493a75c8ed11b9ffccc41f3dd4d"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/AIETJQIY26BJ4EOFQMYDWPJ25A/bundle.json","state_url":"https://pith.science/pith/AIETJQIY26BJ4EOFQMYDWPJ25A/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/AIETJQIY26BJ4EOFQMYDWPJ25A/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":"2026-08-10T02:46:07Z","links":{"resolver":"https://pith.science/pith/AIETJQIY26BJ4EOFQMYDWPJ25A","bundle":"https://pith.science/pith/AIETJQIY26BJ4EOFQMYDWPJ25A/bundle.json","state":"https://pith.science/pith/AIETJQIY26BJ4EOFQMYDWPJ25A/state.json","well_known_bundle":"https://pith.science/.well-known/pith/AIETJQIY26BJ4EOFQMYDWPJ25A/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:AIETJQIY26BJ4EOFQMYDWPJ25A","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":"5b92e6370124c703a504439274dfcfa998ee51c24d00c119ec781af58633b784","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2023-04-13T11:13:19Z","title_canon_sha256":"fe7710d572fddc55d15bfb8f89b3986d7a180bee0766ce24f3be3d691caea831"},"schema_version":"1.0","source":{"id":"2304.06408","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2304.06408","created_at":"2026-07-05T06:26:01Z"},{"alias_kind":"arxiv_version","alias_value":"2304.06408v2","created_at":"2026-07-05T06:26:01Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2304.06408","created_at":"2026-07-05T06:26:01Z"},{"alias_kind":"pith_short_12","alias_value":"AIETJQIY26BJ","created_at":"2026-07-05T06:26:01Z"},{"alias_kind":"pith_short_16","alias_value":"AIETJQIY26BJ4EOF","created_at":"2026-07-05T06:26:01Z"},{"alias_kind":"pith_short_8","alias_value":"AIETJQIY","created_at":"2026-07-05T06:26:01Z"}],"graph_snapshots":[{"event_id":"sha256:421d4cd02fce5cf0d6bb473057d394b9b8b12493a75c8ed11b9ffccc41f3dd4d","target":"graph","created_at":"2026-07-05T06:26:01Z","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/2304.06408/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Detecting fake images is becoming a major goal of computer vision. This need is becoming more and more pressing with the continuous improvement of synthesis methods based on Generative Adversarial Networks (GAN), and even more with the appearance of powerful methods based on Diffusion Models (DM). Towards this end, it is important to gain insight into which image features better discriminate fake images from real ones. In this paper we report on our systematic study of a large number of image generators of different families, aimed at discovering the most forensically relevant characteristics ","authors_text":"Davide Cozzolino, Giovanni Poggi, Koki Nagano, Luisa Verdoliva, Riccardo Corvi","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2023-04-13T11:13:19Z","title":"Intriguing properties of synthetic images: from generative adversarial networks to diffusion models"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2304.06408","kind":"arxiv","version":2},"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:d672fec8dc7e37915a9bbf882effd252ab3f349656b6c3cc706d0a25865855ec","target":"record","created_at":"2026-07-05T06:26:01Z","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":"5b92e6370124c703a504439274dfcfa998ee51c24d00c119ec781af58633b784","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2023-04-13T11:13:19Z","title_canon_sha256":"fe7710d572fddc55d15bfb8f89b3986d7a180bee0766ce24f3be3d691caea831"},"schema_version":"1.0","source":{"id":"2304.06408","kind":"arxiv","version":2}},"canonical_sha256":"020934c118d7829e11c583303b3d3ae8018cd8de2a62e11b7fa0b119744896b5","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"020934c118d7829e11c583303b3d3ae8018cd8de2a62e11b7fa0b119744896b5","first_computed_at":"2026-07-05T06:26:01.585520Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T06:26:01.585520Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"K2pxJtEd5tpODSeQz7Wk3mgjz+ifwJ/u1svIRizshQCBK37gbE3tEeZpdjaknuZx+PZ5VMxzGdntFhd16wR2DA==","signature_status":"signed_v1","signed_at":"2026-07-05T06:26:01.586009Z","signed_message":"canonical_sha256_bytes"},"source_id":"2304.06408","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:d672fec8dc7e37915a9bbf882effd252ab3f349656b6c3cc706d0a25865855ec","sha256:421d4cd02fce5cf0d6bb473057d394b9b8b12493a75c8ed11b9ffccc41f3dd4d"],"state_sha256":"291627881fcd15b91d3c4f1a2265c6996e942128777212afdf7634289b79e284"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"LZIf+QvRmkV+AD1YJap79nHUcJXJ4wmX+5HzmS+H9pag6qWUpziNRWSNhnXvP1jIksB5DCk23uh6821XIJdrAA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-10T02:46:07.092507Z","bundle_sha256":"b9577af49decc7df3c1e89ae4ded944054b83e7aa00cea2e2c0857db81f9876d"}}