{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2022:EZ4NHCSO42YRS2RMWLZPI3Z2JE","short_pith_number":"pith:EZ4NHCSO","canonical_record":{"source":{"id":"2208.10013","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2022-08-22T01:54:23Z","cross_cats_sorted":[],"title_canon_sha256":"628e3bd73ec6613d9a5d19f751ac55f928233fc043681f3e3606f974020ee08e","abstract_canon_sha256":"d99abee983804b0df22593c891c84cc2842dedaba67e01c1cdee1393887dd317"},"schema_version":"1.0"},"canonical_sha256":"2678d38a4ee6b1196a2cb2f2f46f3a491cdfd481da877bc47feac224ef8860d9","source":{"kind":"arxiv","id":"2208.10013","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2208.10013","created_at":"2026-07-05T04:50:24Z"},{"alias_kind":"arxiv_version","alias_value":"2208.10013v1","created_at":"2026-07-05T04:50:24Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2208.10013","created_at":"2026-07-05T04:50:24Z"},{"alias_kind":"pith_short_12","alias_value":"EZ4NHCSO42YR","created_at":"2026-07-05T04:50:24Z"},{"alias_kind":"pith_short_16","alias_value":"EZ4NHCSO42YRS2RM","created_at":"2026-07-05T04:50:24Z"},{"alias_kind":"pith_short_8","alias_value":"EZ4NHCSO","created_at":"2026-07-05T04:50:24Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2022:EZ4NHCSO42YRS2RMWLZPI3Z2JE","target":"record","payload":{"canonical_record":{"source":{"id":"2208.10013","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2022-08-22T01:54:23Z","cross_cats_sorted":[],"title_canon_sha256":"628e3bd73ec6613d9a5d19f751ac55f928233fc043681f3e3606f974020ee08e","abstract_canon_sha256":"d99abee983804b0df22593c891c84cc2842dedaba67e01c1cdee1393887dd317"},"schema_version":"1.0"},"canonical_sha256":"2678d38a4ee6b1196a2cb2f2f46f3a491cdfd481da877bc47feac224ef8860d9","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T04:50:24.276341Z","signature_b64":"Qf+CxfAxWcMVXLGY1Bk0cBXsNJhL+qD5eeODrWotJbWOu3ntpDs5m+yQhjyGXrHs3j2jX0YscWbo3SA4JjT1CA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"2678d38a4ee6b1196a2cb2f2f46f3a491cdfd481da877bc47feac224ef8860d9","last_reissued_at":"2026-07-05T04:50:24.275901Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T04:50:24.275901Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2208.10013","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T04:50:24Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"NAWypA+fCKkm/mCmsZ8ITe86h6LHD5WY9MW9+bPcnXZRYSSz2OJLEguoS+q1YXCTBa8cVKejv84s4Y3jCN7aCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-07T11:58:53.347485Z"},"content_sha256":"1ba07c539b22d8636cd543b0cc173450683bb4dcced8fd30996169584e22608e","schema_version":"1.0","event_id":"sha256:1ba07c539b22d8636cd543b0cc173450683bb4dcced8fd30996169584e22608e"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2022:EZ4NHCSO42YRS2RMWLZPI3Z2JE","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"FairDisCo: Fairer AI in Dermatology via Disentanglement Contrastive Learning","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.CV","authors_text":"Ben Hers, Ghassan Hamarneh, Nourhan Bayasi, Rafeef Garbi, Siyi Du","submitted_at":"2022-08-22T01:54:23Z","abstract_excerpt":"Deep learning models have achieved great success in automating skin lesion diagnosis. However, the ethnic disparity in these models' predictions, where lesions on darker skin types are usually underrepresented and have lower diagnosis accuracy, receives little attention. In this paper, we propose FairDisCo, a disentanglement deep learning framework with contrastive learning that utilizes an additional network branch to remove sensitive attributes, i.e. skin-type information from representations for fairness and another contrastive branch to enhance feature extraction. We compare FairDisCo to t"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2208.10013","kind":"arxiv","version":1},"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/2208.10013/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":"2026-07-05T04:50:24Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"my3a35JiciZIs5xBBXJPymFglGO6ko3JL4PvxYRVjBG4/wANY701C2KrqVSeUl6rmU1CJbRHxD7zMTi/4hBeCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-07T11:58:53.347855Z"},"content_sha256":"964e75f8a06afff9d333349d6e16a149687e92259fe88674c20cab9bfade9177","schema_version":"1.0","event_id":"sha256:964e75f8a06afff9d333349d6e16a149687e92259fe88674c20cab9bfade9177"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/EZ4NHCSO42YRS2RMWLZPI3Z2JE/bundle.json","state_url":"https://pith.science/pith/EZ4NHCSO42YRS2RMWLZPI3Z2JE/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/EZ4NHCSO42YRS2RMWLZPI3Z2JE/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":"2026-07-07T11:58:53Z","links":{"resolver":"https://pith.science/pith/EZ4NHCSO42YRS2RMWLZPI3Z2JE","bundle":"https://pith.science/pith/EZ4NHCSO42YRS2RMWLZPI3Z2JE/bundle.json","state":"https://pith.science/pith/EZ4NHCSO42YRS2RMWLZPI3Z2JE/state.json","well_known_bundle":"https://pith.science/.well-known/pith/EZ4NHCSO42YRS2RMWLZPI3Z2JE/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:EZ4NHCSO42YRS2RMWLZPI3Z2JE","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":"d99abee983804b0df22593c891c84cc2842dedaba67e01c1cdee1393887dd317","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2022-08-22T01:54:23Z","title_canon_sha256":"628e3bd73ec6613d9a5d19f751ac55f928233fc043681f3e3606f974020ee08e"},"schema_version":"1.0","source":{"id":"2208.10013","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2208.10013","created_at":"2026-07-05T04:50:24Z"},{"alias_kind":"arxiv_version","alias_value":"2208.10013v1","created_at":"2026-07-05T04:50:24Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2208.10013","created_at":"2026-07-05T04:50:24Z"},{"alias_kind":"pith_short_12","alias_value":"EZ4NHCSO42YR","created_at":"2026-07-05T04:50:24Z"},{"alias_kind":"pith_short_16","alias_value":"EZ4NHCSO42YRS2RM","created_at":"2026-07-05T04:50:24Z"},{"alias_kind":"pith_short_8","alias_value":"EZ4NHCSO","created_at":"2026-07-05T04:50:24Z"}],"graph_snapshots":[{"event_id":"sha256:964e75f8a06afff9d333349d6e16a149687e92259fe88674c20cab9bfade9177","target":"graph","created_at":"2026-07-05T04:50:24Z","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/2208.10013/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Deep learning models have achieved great success in automating skin lesion diagnosis. However, the ethnic disparity in these models' predictions, where lesions on darker skin types are usually underrepresented and have lower diagnosis accuracy, receives little attention. In this paper, we propose FairDisCo, a disentanglement deep learning framework with contrastive learning that utilizes an additional network branch to remove sensitive attributes, i.e. skin-type information from representations for fairness and another contrastive branch to enhance feature extraction. We compare FairDisCo to t","authors_text":"Ben Hers, Ghassan Hamarneh, Nourhan Bayasi, Rafeef Garbi, Siyi Du","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2022-08-22T01:54:23Z","title":"FairDisCo: Fairer AI in Dermatology via Disentanglement Contrastive Learning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2208.10013","kind":"arxiv","version":1},"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":"sha256:1ba07c539b22d8636cd543b0cc173450683bb4dcced8fd30996169584e22608e","target":"record","created_at":"2026-07-05T04:50:24Z","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":"d99abee983804b0df22593c891c84cc2842dedaba67e01c1cdee1393887dd317","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2022-08-22T01:54:23Z","title_canon_sha256":"628e3bd73ec6613d9a5d19f751ac55f928233fc043681f3e3606f974020ee08e"},"schema_version":"1.0","source":{"id":"2208.10013","kind":"arxiv","version":1}},"canonical_sha256":"2678d38a4ee6b1196a2cb2f2f46f3a491cdfd481da877bc47feac224ef8860d9","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"2678d38a4ee6b1196a2cb2f2f46f3a491cdfd481da877bc47feac224ef8860d9","first_computed_at":"2026-07-05T04:50:24.275901Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T04:50:24.275901Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Qf+CxfAxWcMVXLGY1Bk0cBXsNJhL+qD5eeODrWotJbWOu3ntpDs5m+yQhjyGXrHs3j2jX0YscWbo3SA4JjT1CA==","signature_status":"signed_v1","signed_at":"2026-07-05T04:50:24.276341Z","signed_message":"canonical_sha256_bytes"},"source_id":"2208.10013","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:1ba07c539b22d8636cd543b0cc173450683bb4dcced8fd30996169584e22608e","sha256:964e75f8a06afff9d333349d6e16a149687e92259fe88674c20cab9bfade9177"],"state_sha256":"7bbced6642823f8081d56e175feb4d039e87c237a87f3d408706c0628897a78b"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"pWccKRIsoYMZD/RQUgNmiUg7ir5L5Oc4tjFEtBZCIXbYUzDVJu33tu85+Q2xyInKCAsGalXt0f/Yu8KSnQm8Aw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-07T11:58:53.349837Z","bundle_sha256":"c9ef4ef4b63baa16c7ee4dab44b6460b0bedbcc83a75066506aaad6a1e2401c2"}}