{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2020:RYW3WJ3NMI7LUFIEE43YGWYW6D","short_pith_number":"pith:RYW3WJ3N","canonical_record":{"source":{"id":"2002.03592","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.CV","submitted_at":"2020-02-10T08:17:26Z","cross_cats_sorted":[],"title_canon_sha256":"9ae231c11b9d60127be2ca837cb2733e64d2b139ce81a8a923a02ab173e0f1bc","abstract_canon_sha256":"2b2b06b6ef5e85fb6f54699080ff16bcddea6ad0382e034168d008941e6068d5"},"schema_version":"1.0"},"canonical_sha256":"8e2dbb276d623eba15042737835b16f0e3490a0918376df5918b4b408056a05b","source":{"kind":"arxiv","id":"2002.03592","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2002.03592","created_at":"2026-07-05T01:49:15Z"},{"alias_kind":"arxiv_version","alias_value":"2002.03592v3","created_at":"2026-07-05T01:49:15Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2002.03592","created_at":"2026-07-05T01:49:15Z"},{"alias_kind":"pith_short_12","alias_value":"RYW3WJ3NMI7L","created_at":"2026-07-05T01:49:15Z"},{"alias_kind":"pith_short_16","alias_value":"RYW3WJ3NMI7LUFIE","created_at":"2026-07-05T01:49:15Z"},{"alias_kind":"pith_short_8","alias_value":"RYW3WJ3N","created_at":"2026-07-05T01:49:15Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2020:RYW3WJ3NMI7LUFIEE43YGWYW6D","target":"record","payload":{"canonical_record":{"source":{"id":"2002.03592","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.CV","submitted_at":"2020-02-10T08:17:26Z","cross_cats_sorted":[],"title_canon_sha256":"9ae231c11b9d60127be2ca837cb2733e64d2b139ce81a8a923a02ab173e0f1bc","abstract_canon_sha256":"2b2b06b6ef5e85fb6f54699080ff16bcddea6ad0382e034168d008941e6068d5"},"schema_version":"1.0"},"canonical_sha256":"8e2dbb276d623eba15042737835b16f0e3490a0918376df5918b4b408056a05b","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T01:49:15.189754Z","signature_b64":"MVcuDflHyvrDuDUg18D6x+9jHEwHRnITnigqD4MHFV3ZGmOQGU75HjFzoAyV6XZ/SpSRTtR4uF4mQ8W0LrHoCw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"8e2dbb276d623eba15042737835b16f0e3490a0918376df5918b4b408056a05b","last_reissued_at":"2026-07-05T01:49:15.189297Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T01:49:15.189297Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2002.03592","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":"2026-07-05T01:49:15Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"UnuD5hf9wHsK9QSbQZCmvG8Deg2/6evoBzvpP+Qu6OkE4LJ2DxVQzlE/zfUHraVzzX4ger1BYNup4DN9Mb++Aw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-19T08:00:48.724061Z"},"content_sha256":"55ae9b03bdfae56ae531baf88111cf7537a7b179c08e3041459071cb1c519904","schema_version":"1.0","event_id":"sha256:55ae9b03bdfae56ae531baf88111cf7537a7b179c08e3041459071cb1c519904"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2020:RYW3WJ3NMI7LUFIEE43YGWYW6D","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Post-Comparison Mitigation of Demographic Bias in Face Recognition Using Fair Score Normalization","license":"http://creativecommons.org/licenses/by-sa/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Arjan Kuijper, Florian Kirchbuchner, Jan Niklas Kolf, Naser Damer, Philipp Terh\\\"orst","submitted_at":"2020-02-10T08:17:26Z","abstract_excerpt":"Current face recognition systems achieve high progress on several benchmark tests. Despite this progress, recent works showed that these systems are strongly biased against demographic sub-groups. Consequently, an easily integrable solution is needed to reduce the discriminatory effect of these biased systems. Previous work mainly focused on learning less biased face representations, which comes at the cost of a strongly degraded overall recognition performance. In this work, we propose a novel unsupervised fair score normalization approach that is specifically designed to reduce the effect of"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2002.03592","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/2002.03592/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":"2026-07-05T01:49:15Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"XNRVPf+0rOyUTkA0X1VIW2d5J+ydC2S8wq8nrnX4GWyQb1nyEHKU/BpXC7KuKxV0L6DWceU1YVKRspFws1sHAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-19T08:00:48.724981Z"},"content_sha256":"e9efa936a8f3a73bc900c94638fc16cf8cb0c4ad565896e4ef506b2d3ddbe33d","schema_version":"1.0","event_id":"sha256:e9efa936a8f3a73bc900c94638fc16cf8cb0c4ad565896e4ef506b2d3ddbe33d"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/RYW3WJ3NMI7LUFIEE43YGWYW6D/bundle.json","state_url":"https://pith.science/pith/RYW3WJ3NMI7LUFIEE43YGWYW6D/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/RYW3WJ3NMI7LUFIEE43YGWYW6D/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":"2026-08-19T08:00:48Z","links":{"resolver":"https://pith.science/pith/RYW3WJ3NMI7LUFIEE43YGWYW6D","bundle":"https://pith.science/pith/RYW3WJ3NMI7LUFIEE43YGWYW6D/bundle.json","state":"https://pith.science/pith/RYW3WJ3NMI7LUFIEE43YGWYW6D/state.json","well_known_bundle":"https://pith.science/.well-known/pith/RYW3WJ3NMI7LUFIEE43YGWYW6D/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2020:RYW3WJ3NMI7LUFIEE43YGWYW6D","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":"2b2b06b6ef5e85fb6f54699080ff16bcddea6ad0382e034168d008941e6068d5","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.CV","submitted_at":"2020-02-10T08:17:26Z","title_canon_sha256":"9ae231c11b9d60127be2ca837cb2733e64d2b139ce81a8a923a02ab173e0f1bc"},"schema_version":"1.0","source":{"id":"2002.03592","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2002.03592","created_at":"2026-07-05T01:49:15Z"},{"alias_kind":"arxiv_version","alias_value":"2002.03592v3","created_at":"2026-07-05T01:49:15Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2002.03592","created_at":"2026-07-05T01:49:15Z"},{"alias_kind":"pith_short_12","alias_value":"RYW3WJ3NMI7L","created_at":"2026-07-05T01:49:15Z"},{"alias_kind":"pith_short_16","alias_value":"RYW3WJ3NMI7LUFIE","created_at":"2026-07-05T01:49:15Z"},{"alias_kind":"pith_short_8","alias_value":"RYW3WJ3N","created_at":"2026-07-05T01:49:15Z"}],"graph_snapshots":[{"event_id":"sha256:e9efa936a8f3a73bc900c94638fc16cf8cb0c4ad565896e4ef506b2d3ddbe33d","target":"graph","created_at":"2026-07-05T01:49:15Z","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/2002.03592/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Current face recognition systems achieve high progress on several benchmark tests. Despite this progress, recent works showed that these systems are strongly biased against demographic sub-groups. Consequently, an easily integrable solution is needed to reduce the discriminatory effect of these biased systems. Previous work mainly focused on learning less biased face representations, which comes at the cost of a strongly degraded overall recognition performance. In this work, we propose a novel unsupervised fair score normalization approach that is specifically designed to reduce the effect of","authors_text":"Arjan Kuijper, Florian Kirchbuchner, Jan Niklas Kolf, Naser Damer, Philipp Terh\\\"orst","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.CV","submitted_at":"2020-02-10T08:17:26Z","title":"Post-Comparison Mitigation of Demographic Bias in Face Recognition Using Fair Score Normalization"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2002.03592","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":"sha256:55ae9b03bdfae56ae531baf88111cf7537a7b179c08e3041459071cb1c519904","target":"record","created_at":"2026-07-05T01:49:15Z","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":"2b2b06b6ef5e85fb6f54699080ff16bcddea6ad0382e034168d008941e6068d5","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.CV","submitted_at":"2020-02-10T08:17:26Z","title_canon_sha256":"9ae231c11b9d60127be2ca837cb2733e64d2b139ce81a8a923a02ab173e0f1bc"},"schema_version":"1.0","source":{"id":"2002.03592","kind":"arxiv","version":3}},"canonical_sha256":"8e2dbb276d623eba15042737835b16f0e3490a0918376df5918b4b408056a05b","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"8e2dbb276d623eba15042737835b16f0e3490a0918376df5918b4b408056a05b","first_computed_at":"2026-07-05T01:49:15.189297Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T01:49:15.189297Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"MVcuDflHyvrDuDUg18D6x+9jHEwHRnITnigqD4MHFV3ZGmOQGU75HjFzoAyV6XZ/SpSRTtR4uF4mQ8W0LrHoCw==","signature_status":"signed_v1","signed_at":"2026-07-05T01:49:15.189754Z","signed_message":"canonical_sha256_bytes"},"source_id":"2002.03592","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:55ae9b03bdfae56ae531baf88111cf7537a7b179c08e3041459071cb1c519904","sha256:e9efa936a8f3a73bc900c94638fc16cf8cb0c4ad565896e4ef506b2d3ddbe33d"],"state_sha256":"c22e79454c38728ed281826a281573858719a46a8f53843278779f9948799a58"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"6+pQfKGOIGpH/JWv0GuJuPcN9Y3M4DwxShs1xhANpjKA8wcvvHq0z82GzJxnWS2bS8D8gtb+LDdg6ELg4fn7DA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-19T08:00:48.733292Z","bundle_sha256":"92eda3bc85366c03104e8513f23cd3bac67de454c25d413f2a139bc80bdaedd0"}}