{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2019:WMJWMN6QO7NMMHRVLWCJMWSKZF","short_pith_number":"pith:WMJWMN6Q","canonical_record":{"source":{"id":"1907.08175","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-07-11T17:41:57Z","cross_cats_sorted":["cs.LG","eess.IV","stat.ML"],"title_canon_sha256":"0a0650442c264254556e08e323b6a43ae92c9422ce262648dc9890130ae524f1","abstract_canon_sha256":"85a34879da5f6bad2c17b0a3cbc4bd68ff89ad035567dafa349b9224a51eaf4d"},"schema_version":"1.0"},"canonical_sha256":"b3136637d077dac61e355d84965a4ac94f1efeab4e638f0b222ff6c2781a3b4a","source":{"kind":"arxiv","id":"1907.08175","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1907.08175","created_at":"2026-07-05T00:28:10Z"},{"alias_kind":"arxiv_version","alias_value":"1907.08175v3","created_at":"2026-07-05T00:28:10Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1907.08175","created_at":"2026-07-05T00:28:10Z"},{"alias_kind":"pith_short_12","alias_value":"WMJWMN6QO7NM","created_at":"2026-07-05T00:28:10Z"},{"alias_kind":"pith_short_16","alias_value":"WMJWMN6QO7NMMHRV","created_at":"2026-07-05T00:28:10Z"},{"alias_kind":"pith_short_8","alias_value":"WMJWMN6Q","created_at":"2026-07-05T00:28:10Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2019:WMJWMN6QO7NMMHRVLWCJMWSKZF","target":"record","payload":{"canonical_record":{"source":{"id":"1907.08175","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-07-11T17:41:57Z","cross_cats_sorted":["cs.LG","eess.IV","stat.ML"],"title_canon_sha256":"0a0650442c264254556e08e323b6a43ae92c9422ce262648dc9890130ae524f1","abstract_canon_sha256":"85a34879da5f6bad2c17b0a3cbc4bd68ff89ad035567dafa349b9224a51eaf4d"},"schema_version":"1.0"},"canonical_sha256":"b3136637d077dac61e355d84965a4ac94f1efeab4e638f0b222ff6c2781a3b4a","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T00:28:10.695088Z","signature_b64":"MrIInUsZA7VlZfTzu6B1EMbBzfsjFfQVCAJ8F6blVWVKXqbADtgUiSmKozMznTkH8qYDsyewaQuZsZqpBDxwDg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"b3136637d077dac61e355d84965a4ac94f1efeab4e638f0b222ff6c2781a3b4a","last_reissued_at":"2026-07-05T00:28:10.694575Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T00:28:10.694575Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1907.08175","source_version":3,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T00:28:10Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"0mzqUP9M1R7tUK3oxDzsbremaQrlu8EO1NPN/LROTHJVYiIJbOEDP4TbuXGhRfUICvtGoWOO/LCtbvHj7k3GAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-10T08:25:09.919808Z"},"content_sha256":"ec2f42de51d7a8350df4de656efa1eae8928c3fa8a27ac48587866d075f1cc81","schema_version":"1.0","event_id":"sha256:ec2f42de51d7a8350df4de656efa1eae8928c3fa8a27ac48587866d075f1cc81"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2019:WMJWMN6QO7NMMHRVLWCJMWSKZF","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"On the Evaluation of Conditional GANs","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG","eess.IV","stat.ML"],"primary_cat":"cs.CV","authors_text":"Adriana Romero, Graham W. Taylor, Luis Pineda, Michal Drozdzal, Terrance DeVries","submitted_at":"2019-07-11T17:41:57Z","abstract_excerpt":"Conditional Generative Adversarial Networks (cGANs) are finding increasingly widespread use in many application domains. Despite outstanding progress, quantitative evaluation of such models often involves multiple distinct metrics to assess different desirable properties, such as image quality, conditional consistency, and intra-conditioning diversity. In this setting, model benchmarking becomes a challenge, as each metric may indicate a different \"best\" model. In this paper, we propose the Frechet Joint Distance (FJD), which is defined as the Frechet distance between joint distributions of im"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1907.08175","kind":"arxiv","version":3},"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/1907.08175/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":"2026-07-05T00:28:10Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"LoWdcdbP+NOrtP0BBO/2ua78TmBVO5vvq+WKoEWTbOUrxI2T1vwQfyJ2dA9RHT5KlMmsuHtEAvm8+OQJxvhXCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-10T08:25:09.920862Z"},"content_sha256":"a5db5572eab58178d2eaf825ecb04dd1943eaa9c9390e860b3c4279248474af8","schema_version":"1.0","event_id":"sha256:a5db5572eab58178d2eaf825ecb04dd1943eaa9c9390e860b3c4279248474af8"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/WMJWMN6QO7NMMHRVLWCJMWSKZF/bundle.json","state_url":"https://pith.science/pith/WMJWMN6QO7NMMHRVLWCJMWSKZF/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/WMJWMN6QO7NMMHRVLWCJMWSKZF/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":"2026-08-10T08:25:09Z","links":{"resolver":"https://pith.science/pith/WMJWMN6QO7NMMHRVLWCJMWSKZF","bundle":"https://pith.science/pith/WMJWMN6QO7NMMHRVLWCJMWSKZF/bundle.json","state":"https://pith.science/pith/WMJWMN6QO7NMMHRVLWCJMWSKZF/state.json","well_known_bundle":"https://pith.science/.well-known/pith/WMJWMN6QO7NMMHRVLWCJMWSKZF/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:WMJWMN6QO7NMMHRVLWCJMWSKZF","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":"85a34879da5f6bad2c17b0a3cbc4bd68ff89ad035567dafa349b9224a51eaf4d","cross_cats_sorted":["cs.LG","eess.IV","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-07-11T17:41:57Z","title_canon_sha256":"0a0650442c264254556e08e323b6a43ae92c9422ce262648dc9890130ae524f1"},"schema_version":"1.0","source":{"id":"1907.08175","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1907.08175","created_at":"2026-07-05T00:28:10Z"},{"alias_kind":"arxiv_version","alias_value":"1907.08175v3","created_at":"2026-07-05T00:28:10Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1907.08175","created_at":"2026-07-05T00:28:10Z"},{"alias_kind":"pith_short_12","alias_value":"WMJWMN6QO7NM","created_at":"2026-07-05T00:28:10Z"},{"alias_kind":"pith_short_16","alias_value":"WMJWMN6QO7NMMHRV","created_at":"2026-07-05T00:28:10Z"},{"alias_kind":"pith_short_8","alias_value":"WMJWMN6Q","created_at":"2026-07-05T00:28:10Z"}],"graph_snapshots":[{"event_id":"sha256:a5db5572eab58178d2eaf825ecb04dd1943eaa9c9390e860b3c4279248474af8","target":"graph","created_at":"2026-07-05T00:28:10Z","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/1907.08175/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Conditional Generative Adversarial Networks (cGANs) are finding increasingly widespread use in many application domains. Despite outstanding progress, quantitative evaluation of such models often involves multiple distinct metrics to assess different desirable properties, such as image quality, conditional consistency, and intra-conditioning diversity. In this setting, model benchmarking becomes a challenge, as each metric may indicate a different \"best\" model. In this paper, we propose the Frechet Joint Distance (FJD), which is defined as the Frechet distance between joint distributions of im","authors_text":"Adriana Romero, Graham W. Taylor, Luis Pineda, Michal Drozdzal, Terrance DeVries","cross_cats":["cs.LG","eess.IV","stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-07-11T17:41:57Z","title":"On the Evaluation of Conditional GANs"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1907.08175","kind":"arxiv","version":3},"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:ec2f42de51d7a8350df4de656efa1eae8928c3fa8a27ac48587866d075f1cc81","target":"record","created_at":"2026-07-05T00:28:10Z","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":"85a34879da5f6bad2c17b0a3cbc4bd68ff89ad035567dafa349b9224a51eaf4d","cross_cats_sorted":["cs.LG","eess.IV","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-07-11T17:41:57Z","title_canon_sha256":"0a0650442c264254556e08e323b6a43ae92c9422ce262648dc9890130ae524f1"},"schema_version":"1.0","source":{"id":"1907.08175","kind":"arxiv","version":3}},"canonical_sha256":"b3136637d077dac61e355d84965a4ac94f1efeab4e638f0b222ff6c2781a3b4a","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"b3136637d077dac61e355d84965a4ac94f1efeab4e638f0b222ff6c2781a3b4a","first_computed_at":"2026-07-05T00:28:10.694575Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T00:28:10.694575Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"MrIInUsZA7VlZfTzu6B1EMbBzfsjFfQVCAJ8F6blVWVKXqbADtgUiSmKozMznTkH8qYDsyewaQuZsZqpBDxwDg==","signature_status":"signed_v1","signed_at":"2026-07-05T00:28:10.695088Z","signed_message":"canonical_sha256_bytes"},"source_id":"1907.08175","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:ec2f42de51d7a8350df4de656efa1eae8928c3fa8a27ac48587866d075f1cc81","sha256:a5db5572eab58178d2eaf825ecb04dd1943eaa9c9390e860b3c4279248474af8"],"state_sha256":"753fe08aa8fda915b561fd198850d09a40cc0c1bb831abfebf98dd61288f586f"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"S3ne5IbGTrvGc6dRnZ9LwrI4SOz+o5XXNQnt7hp7eEHuj8ZDIDdsQTN25EOwPUjCHt6Ywn4e741pfGwE5m/eAw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-10T08:25:09.927200Z","bundle_sha256":"7c3812412730dacc8431c11cb01cb5181cdf5c4d7786e0b9cab28c51206cecfb"}}