{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2021:VA2ZBKNLASOWELEKXC6LGTGJHU","short_pith_number":"pith:VA2ZBKNL","canonical_record":{"source":{"id":"2105.04580","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2021-05-10T18:00:13Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"2ccd83c0bf3b3f9453421590687403aafd4e0e3d0a8c52fd2b10d95e25264895","abstract_canon_sha256":"4e968d7ecd0a14c54574e72532b723b40730cd975e8255dcbb38f0f9d133fbe5"},"schema_version":"1.0"},"canonical_sha256":"a83590a9ab049d622c8ab8bcb34cc93d040a7666df9c1b871b1c39f9f7ce786c","source":{"kind":"arxiv","id":"2105.04580","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2105.04580","created_at":"2026-07-05T03:15:52Z"},{"alias_kind":"arxiv_version","alias_value":"2105.04580v2","created_at":"2026-07-05T03:15:52Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2105.04580","created_at":"2026-07-05T03:15:52Z"},{"alias_kind":"pith_short_12","alias_value":"VA2ZBKNLASOW","created_at":"2026-07-05T03:15:52Z"},{"alias_kind":"pith_short_16","alias_value":"VA2ZBKNLASOWELEK","created_at":"2026-07-05T03:15:52Z"},{"alias_kind":"pith_short_8","alias_value":"VA2ZBKNL","created_at":"2026-07-05T03:15:52Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2021:VA2ZBKNLASOWELEKXC6LGTGJHU","target":"record","payload":{"canonical_record":{"source":{"id":"2105.04580","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2021-05-10T18:00:13Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"2ccd83c0bf3b3f9453421590687403aafd4e0e3d0a8c52fd2b10d95e25264895","abstract_canon_sha256":"4e968d7ecd0a14c54574e72532b723b40730cd975e8255dcbb38f0f9d133fbe5"},"schema_version":"1.0"},"canonical_sha256":"a83590a9ab049d622c8ab8bcb34cc93d040a7666df9c1b871b1c39f9f7ce786c","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T03:15:52.655227Z","signature_b64":"GSZ6HEzjT/Fhth4v6EJ5jc6ej84xeTdsOSQGOS8Xh49FfBCe3AJDenavyeMrnXo604TvdmjWSRO1Ym4ljWLNBA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"a83590a9ab049d622c8ab8bcb34cc93d040a7666df9c1b871b1c39f9f7ce786c","last_reissued_at":"2026-07-05T03:15:52.654790Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T03:15:52.654790Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2105.04580","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":"2026-07-05T03:15:52Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"cm7Yxl0F0aKNbZdW3K1LQrfrr9lTURRnCbekr/TaZV9w+jLFfHgVQabcjPh4LdQYH5TOkmzCwaL1wdlrwXprCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-07T18:05:49.891731Z"},"content_sha256":"791b3efca6cd9e5a7476b9b87dd5ecbc81ba1f29e8a0d82f05408c8b1933074e","schema_version":"1.0","event_id":"sha256:791b3efca6cd9e5a7476b9b87dd5ecbc81ba1f29e8a0d82f05408c8b1933074e"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2021:VA2ZBKNLASOWELEKXC6LGTGJHU","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Towards Discovery and Attribution of Open-world GAN Generated Images","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"cs.CV","authors_text":"Abhinav Shrivastava, Saketh Rambhatla, Saksham Suri, Sharath Girish","submitted_at":"2021-05-10T18:00:13Z","abstract_excerpt":"With the recent progress in Generative Adversarial Networks (GANs), it is imperative for media and visual forensics to develop detectors which can identify and attribute images to the model generating them. Existing works have shown to attribute images to their corresponding GAN sources with high accuracy. However, these works are limited to a closed set scenario, failing to generalize to GANs unseen during train time and are therefore, not scalable with a steady influx of new GANs. We present an iterative algorithm for discovering images generated from previously unseen GANs by exploiting the"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2105.04580","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/2105.04580/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":"2026-07-05T03:15:52Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"AwWKS9pl8kCrZDzcpQUSubI9xbIO2TYeCmGAeW+GtXKyeXrR6+0aBz45Uj2y3rr25KS/yYApovoKSD3fTihnBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-07T18:05:49.892237Z"},"content_sha256":"82c81b54ed6c33f8997f59c1e0a21140ee8c46aefb4d9f92d7d7078fa4cf3823","schema_version":"1.0","event_id":"sha256:82c81b54ed6c33f8997f59c1e0a21140ee8c46aefb4d9f92d7d7078fa4cf3823"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/VA2ZBKNLASOWELEKXC6LGTGJHU/bundle.json","state_url":"https://pith.science/pith/VA2ZBKNLASOWELEKXC6LGTGJHU/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/VA2ZBKNLASOWELEKXC6LGTGJHU/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":"2026-08-07T18:05:49Z","links":{"resolver":"https://pith.science/pith/VA2ZBKNLASOWELEKXC6LGTGJHU","bundle":"https://pith.science/pith/VA2ZBKNLASOWELEKXC6LGTGJHU/bundle.json","state":"https://pith.science/pith/VA2ZBKNLASOWELEKXC6LGTGJHU/state.json","well_known_bundle":"https://pith.science/.well-known/pith/VA2ZBKNLASOWELEKXC6LGTGJHU/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2021:VA2ZBKNLASOWELEKXC6LGTGJHU","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":"4e968d7ecd0a14c54574e72532b723b40730cd975e8255dcbb38f0f9d133fbe5","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2021-05-10T18:00:13Z","title_canon_sha256":"2ccd83c0bf3b3f9453421590687403aafd4e0e3d0a8c52fd2b10d95e25264895"},"schema_version":"1.0","source":{"id":"2105.04580","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2105.04580","created_at":"2026-07-05T03:15:52Z"},{"alias_kind":"arxiv_version","alias_value":"2105.04580v2","created_at":"2026-07-05T03:15:52Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2105.04580","created_at":"2026-07-05T03:15:52Z"},{"alias_kind":"pith_short_12","alias_value":"VA2ZBKNLASOW","created_at":"2026-07-05T03:15:52Z"},{"alias_kind":"pith_short_16","alias_value":"VA2ZBKNLASOWELEK","created_at":"2026-07-05T03:15:52Z"},{"alias_kind":"pith_short_8","alias_value":"VA2ZBKNL","created_at":"2026-07-05T03:15:52Z"}],"graph_snapshots":[{"event_id":"sha256:82c81b54ed6c33f8997f59c1e0a21140ee8c46aefb4d9f92d7d7078fa4cf3823","target":"graph","created_at":"2026-07-05T03:15:52Z","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/2105.04580/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"With the recent progress in Generative Adversarial Networks (GANs), it is imperative for media and visual forensics to develop detectors which can identify and attribute images to the model generating them. Existing works have shown to attribute images to their corresponding GAN sources with high accuracy. However, these works are limited to a closed set scenario, failing to generalize to GANs unseen during train time and are therefore, not scalable with a steady influx of new GANs. We present an iterative algorithm for discovering images generated from previously unseen GANs by exploiting the","authors_text":"Abhinav Shrivastava, Saketh Rambhatla, Saksham Suri, Sharath Girish","cross_cats":["cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2021-05-10T18:00:13Z","title":"Towards Discovery and Attribution of Open-world GAN Generated Images"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2105.04580","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":"sha256:791b3efca6cd9e5a7476b9b87dd5ecbc81ba1f29e8a0d82f05408c8b1933074e","target":"record","created_at":"2026-07-05T03:15:52Z","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":"4e968d7ecd0a14c54574e72532b723b40730cd975e8255dcbb38f0f9d133fbe5","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2021-05-10T18:00:13Z","title_canon_sha256":"2ccd83c0bf3b3f9453421590687403aafd4e0e3d0a8c52fd2b10d95e25264895"},"schema_version":"1.0","source":{"id":"2105.04580","kind":"arxiv","version":2}},"canonical_sha256":"a83590a9ab049d622c8ab8bcb34cc93d040a7666df9c1b871b1c39f9f7ce786c","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"a83590a9ab049d622c8ab8bcb34cc93d040a7666df9c1b871b1c39f9f7ce786c","first_computed_at":"2026-07-05T03:15:52.654790Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T03:15:52.654790Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"GSZ6HEzjT/Fhth4v6EJ5jc6ej84xeTdsOSQGOS8Xh49FfBCe3AJDenavyeMrnXo604TvdmjWSRO1Ym4ljWLNBA==","signature_status":"signed_v1","signed_at":"2026-07-05T03:15:52.655227Z","signed_message":"canonical_sha256_bytes"},"source_id":"2105.04580","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:791b3efca6cd9e5a7476b9b87dd5ecbc81ba1f29e8a0d82f05408c8b1933074e","sha256:82c81b54ed6c33f8997f59c1e0a21140ee8c46aefb4d9f92d7d7078fa4cf3823"],"state_sha256":"f960ed9a79ef8dea8d8930754ac5e1150859ed735bde781fb0937b08cc1830e3"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"mdhViaZksAN3dmO0GzcZhNPni8T0uti9L+k6c+fXIPIhMnQiVs2cRCp1lTRauHg4rQjuyr4yW0dOFW+b2vHfAQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-07T18:05:49.896689Z","bundle_sha256":"21cbc112dff0ff04e1ac0e21ddba4cb441efbee9d864c8e0dd1bb948218806f9"}}