{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:XY4E22JDHTNY47VA3HFCEHVF67","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":"61a3e6dffd1ed3f6c8d4efe5601eec30dffb07126a47441bf54531b4d5a86f3d","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-05-01T19:43:12Z","title_canon_sha256":"55209cecbfbca4c276b416193c6cc796cfe99ce4895b6119ec8418bb082e4010"},"schema_version":"1.0","source":{"id":"2505.00830","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2505.00830","created_at":"2026-07-05T11:46:21Z"},{"alias_kind":"arxiv_version","alias_value":"2505.00830v2","created_at":"2026-07-05T11:46:21Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2505.00830","created_at":"2026-07-05T11:46:21Z"},{"alias_kind":"pith_short_12","alias_value":"XY4E22JDHTNY","created_at":"2026-07-05T11:46:21Z"},{"alias_kind":"pith_short_16","alias_value":"XY4E22JDHTNY47VA","created_at":"2026-07-05T11:46:21Z"},{"alias_kind":"pith_short_8","alias_value":"XY4E22JD","created_at":"2026-07-05T11:46:21Z"}],"graph_snapshots":[{"event_id":"sha256:f3bb41a9e57ad5a7f0c8952bb9e0c9d7c86489f963accea8814761db1dd92847","target":"graph","created_at":"2026-07-05T11:46:21Z","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/2505.00830/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Fairness in machine learning research is commonly framed in the context of classification tasks, leaving critical gaps in regression. In this paper, we propose a novel approach to measure intersectional fairness in regression tasks, going beyond the focus on single protected attributes from existing work to consider combinations of all protected attributes. Furthermore, we contend that it is insufficient to measure the average error of groups without regard for imbalanced domain preferences. Accordingly, we propose Intersectional Divergence (ID) as the first fairness measure for regression tas","authors_text":"Joe Germino, Nitesh V. Chawla, Nuno Moniz","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-05-01T19:43:12Z","title":"Intersectional Divergence: Measuring Fairness in Regression"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2505.00830","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":"sha256:54ad1ce48e2c11774e869ee4604816deb5148dab1117355731ae3d2f7b452ef4","target":"record","created_at":"2026-07-05T11:46:21Z","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":"61a3e6dffd1ed3f6c8d4efe5601eec30dffb07126a47441bf54531b4d5a86f3d","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2025-05-01T19:43:12Z","title_canon_sha256":"55209cecbfbca4c276b416193c6cc796cfe99ce4895b6119ec8418bb082e4010"},"schema_version":"1.0","source":{"id":"2505.00830","kind":"arxiv","version":2}},"canonical_sha256":"be384d69233cdb8e7ea0d9ca221ea5f7c21242ee149489d071feb2f9dda4c0ff","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"be384d69233cdb8e7ea0d9ca221ea5f7c21242ee149489d071feb2f9dda4c0ff","first_computed_at":"2026-07-05T11:46:21.901611Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:46:21.901611Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"9Sf+1GeM6imTKFrDtsLCD7fn0a61RKY6FSVkomK2yTyP57B7uUgGpg0g/nCC2iskLvZgCJfzvvgq9Ndg/kkmDg==","signature_status":"signed_v1","signed_at":"2026-07-05T11:46:21.902114Z","signed_message":"canonical_sha256_bytes"},"source_id":"2505.00830","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:54ad1ce48e2c11774e869ee4604816deb5148dab1117355731ae3d2f7b452ef4","sha256:f3bb41a9e57ad5a7f0c8952bb9e0c9d7c86489f963accea8814761db1dd92847"],"state_sha256":"cf91eb51e876e3fe5b94857a6f3890f7ca63491603b79e17476d7241157eeb7e"}