{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:2NIMQORTKKXG534SRYWIDW2XVE","short_pith_number":"pith:2NIMQORT","canonical_record":{"source":{"id":"2412.16373","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2024-12-20T22:17:57Z","cross_cats_sorted":["cs.AI","cs.CY"],"title_canon_sha256":"aa376928997ceaa4b1ef5dc5b7c87e153cdec67648c20857877dddd47dc1b293","abstract_canon_sha256":"d0938c05ce38c5d8b0daf2cd0e03cd601e2b2456587298edfe8ae14f1f8634ef"},"schema_version":"1.0"},"canonical_sha256":"d350c83a3352ae6eef928e2c81db57a9026fb899e3e4bce689ea8ae821af441f","source":{"kind":"arxiv","id":"2412.16373","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2412.16373","created_at":"2026-07-05T11:09:05Z"},{"alias_kind":"arxiv_version","alias_value":"2412.16373v2","created_at":"2026-07-05T11:09:05Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2412.16373","created_at":"2026-07-05T11:09:05Z"},{"alias_kind":"pith_short_12","alias_value":"2NIMQORTKKXG","created_at":"2026-07-05T11:09:05Z"},{"alias_kind":"pith_short_16","alias_value":"2NIMQORTKKXG534S","created_at":"2026-07-05T11:09:05Z"},{"alias_kind":"pith_short_8","alias_value":"2NIMQORT","created_at":"2026-07-05T11:09:05Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:2NIMQORTKKXG534SRYWIDW2XVE","target":"record","payload":{"canonical_record":{"source":{"id":"2412.16373","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2024-12-20T22:17:57Z","cross_cats_sorted":["cs.AI","cs.CY"],"title_canon_sha256":"aa376928997ceaa4b1ef5dc5b7c87e153cdec67648c20857877dddd47dc1b293","abstract_canon_sha256":"d0938c05ce38c5d8b0daf2cd0e03cd601e2b2456587298edfe8ae14f1f8634ef"},"schema_version":"1.0"},"canonical_sha256":"d350c83a3352ae6eef928e2c81db57a9026fb899e3e4bce689ea8ae821af441f","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:09:05.679800Z","signature_b64":"l9DCZyvphsW7DEomDfZHB9AJHoXrQjXl8pQsmceBB2UAWOG7I2uCXuuGT2Ajf+iykeKxA4CsBKBhpu/l9kZGBQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"d350c83a3352ae6eef928e2c81db57a9026fb899e3e4bce689ea8ae821af441f","last_reissued_at":"2026-07-05T11:09:05.679327Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:09:05.679327Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2412.16373","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":"2026-07-05T11:09:05Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"tf1ZlQbInISqoBkJ41vV6QnS19WPbKCNsi73+LZmnsdf0LY3925mxULwrKTPOnJTIJa/K2mqGvAslSeiuPtMDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-14T01:11:06.105008Z"},"content_sha256":"1b040d431bf6cb1043f128619f6a6893cfd8426ddeb73dd8dd7d065422d4cd23","schema_version":"1.0","event_id":"sha256:1b040d431bf6cb1043f128619f6a6893cfd8426ddeb73dd8dd7d065422d4cd23"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:2NIMQORTKKXG534SRYWIDW2XVE","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"FairREAD: Re-fusing Demographic Attributes after Disentanglement for Fair Medical Image Classification","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI","cs.CY"],"primary_cat":"cs.CV","authors_text":"Bo Zhou, Jinkui Hao, Yicheng Gao","submitted_at":"2024-12-20T22:17:57Z","abstract_excerpt":"Recent advancements in deep learning have shown transformative potential in medical imaging, yet concerns about fairness persist due to performance disparities across demographic subgroups. Existing methods aim to address these biases by mitigating sensitive attributes in image data; however, these attributes often carry clinically relevant information, and their removal can compromise model performance-a highly undesirable outcome. To address this challenge, we propose Fair Re-fusion After Disentanglement (FairREAD), a novel, simple, and efficient framework that mitigates unfairness by re-int"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2412.16373","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/2412.16373/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":"2026-07-05T11:09:05Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"j0s6V3IwDBtnbQPmez/04vhcMPLfKldghMeHOjWu14weowDrurhKoPT+1uB8xMEEljqMmw5+5mG7FLNUtCD/Ag==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-14T01:11:06.105957Z"},"content_sha256":"115c202ee49c79ee5f10311502f29c3c848f9c58784056c679da75e3afd7cbad","schema_version":"1.0","event_id":"sha256:115c202ee49c79ee5f10311502f29c3c848f9c58784056c679da75e3afd7cbad"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/2NIMQORTKKXG534SRYWIDW2XVE/bundle.json","state_url":"https://pith.science/pith/2NIMQORTKKXG534SRYWIDW2XVE/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/2NIMQORTKKXG534SRYWIDW2XVE/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":"2026-08-14T01:11:06Z","links":{"resolver":"https://pith.science/pith/2NIMQORTKKXG534SRYWIDW2XVE","bundle":"https://pith.science/pith/2NIMQORTKKXG534SRYWIDW2XVE/bundle.json","state":"https://pith.science/pith/2NIMQORTKKXG534SRYWIDW2XVE/state.json","well_known_bundle":"https://pith.science/.well-known/pith/2NIMQORTKKXG534SRYWIDW2XVE/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:2NIMQORTKKXG534SRYWIDW2XVE","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":"d0938c05ce38c5d8b0daf2cd0e03cd601e2b2456587298edfe8ae14f1f8634ef","cross_cats_sorted":["cs.AI","cs.CY"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2024-12-20T22:17:57Z","title_canon_sha256":"aa376928997ceaa4b1ef5dc5b7c87e153cdec67648c20857877dddd47dc1b293"},"schema_version":"1.0","source":{"id":"2412.16373","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2412.16373","created_at":"2026-07-05T11:09:05Z"},{"alias_kind":"arxiv_version","alias_value":"2412.16373v2","created_at":"2026-07-05T11:09:05Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2412.16373","created_at":"2026-07-05T11:09:05Z"},{"alias_kind":"pith_short_12","alias_value":"2NIMQORTKKXG","created_at":"2026-07-05T11:09:05Z"},{"alias_kind":"pith_short_16","alias_value":"2NIMQORTKKXG534S","created_at":"2026-07-05T11:09:05Z"},{"alias_kind":"pith_short_8","alias_value":"2NIMQORT","created_at":"2026-07-05T11:09:05Z"}],"graph_snapshots":[{"event_id":"sha256:115c202ee49c79ee5f10311502f29c3c848f9c58784056c679da75e3afd7cbad","target":"graph","created_at":"2026-07-05T11:09:05Z","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/2412.16373/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Recent advancements in deep learning have shown transformative potential in medical imaging, yet concerns about fairness persist due to performance disparities across demographic subgroups. Existing methods aim to address these biases by mitigating sensitive attributes in image data; however, these attributes often carry clinically relevant information, and their removal can compromise model performance-a highly undesirable outcome. To address this challenge, we propose Fair Re-fusion After Disentanglement (FairREAD), a novel, simple, and efficient framework that mitigates unfairness by re-int","authors_text":"Bo Zhou, Jinkui Hao, Yicheng Gao","cross_cats":["cs.AI","cs.CY"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2024-12-20T22:17:57Z","title":"FairREAD: Re-fusing Demographic Attributes after Disentanglement for Fair Medical Image Classification"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2412.16373","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":"sha256:1b040d431bf6cb1043f128619f6a6893cfd8426ddeb73dd8dd7d065422d4cd23","target":"record","created_at":"2026-07-05T11:09:05Z","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":"d0938c05ce38c5d8b0daf2cd0e03cd601e2b2456587298edfe8ae14f1f8634ef","cross_cats_sorted":["cs.AI","cs.CY"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CV","submitted_at":"2024-12-20T22:17:57Z","title_canon_sha256":"aa376928997ceaa4b1ef5dc5b7c87e153cdec67648c20857877dddd47dc1b293"},"schema_version":"1.0","source":{"id":"2412.16373","kind":"arxiv","version":2}},"canonical_sha256":"d350c83a3352ae6eef928e2c81db57a9026fb899e3e4bce689ea8ae821af441f","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"d350c83a3352ae6eef928e2c81db57a9026fb899e3e4bce689ea8ae821af441f","first_computed_at":"2026-07-05T11:09:05.679327Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:09:05.679327Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"l9DCZyvphsW7DEomDfZHB9AJHoXrQjXl8pQsmceBB2UAWOG7I2uCXuuGT2Ajf+iykeKxA4CsBKBhpu/l9kZGBQ==","signature_status":"signed_v1","signed_at":"2026-07-05T11:09:05.679800Z","signed_message":"canonical_sha256_bytes"},"source_id":"2412.16373","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:1b040d431bf6cb1043f128619f6a6893cfd8426ddeb73dd8dd7d065422d4cd23","sha256:115c202ee49c79ee5f10311502f29c3c848f9c58784056c679da75e3afd7cbad"],"state_sha256":"ac92b788262c2f671e5bede7fafcd69c4aecbfb1243f7398add05431f5686fd1"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"TvJUuxpQpr7UjKmpkb1NBpyuD0xDouUxtjf/P0FMSR96DPIct7s8NG5i5WjiD8KDIyvw3PeD6dLSB6Lq7+slCA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-14T01:11:06.114115Z","bundle_sha256":"1d729b64794afc8deb7c025d7256e6191e0aa5716bcf9e55fc0d356c0a769db7"}}