{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:GTIGR3QBBV7G5UYXM73WWRSXXN","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":"5cfaa034503f04a44bf93f2b081ff3fe4cba6f7431209d7ed1675e2668b8fe65","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-09-23T00:31:39Z","title_canon_sha256":"339de17aad39a5cf6afc888a1ee880ba2e1197c4406c6f7bd6d0c0337248c343"},"schema_version":"1.0","source":{"id":"2409.14637","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2409.14637","created_at":"2026-07-05T09:10:19Z"},{"alias_kind":"arxiv_version","alias_value":"2409.14637v1","created_at":"2026-07-05T09:10:19Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2409.14637","created_at":"2026-07-05T09:10:19Z"},{"alias_kind":"pith_short_12","alias_value":"GTIGR3QBBV7G","created_at":"2026-07-05T09:10:19Z"},{"alias_kind":"pith_short_16","alias_value":"GTIGR3QBBV7G5UYX","created_at":"2026-07-05T09:10:19Z"},{"alias_kind":"pith_short_8","alias_value":"GTIGR3QB","created_at":"2026-07-05T09:10:19Z"}],"graph_snapshots":[{"event_id":"sha256:2263181dc732c2a27413b5f054e585f0e96c66ceab19f67e3e8213932855cdbe","target":"graph","created_at":"2026-07-05T09:10:19Z","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/2409.14637/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Spurious correlations are a major source of errors for machine learning models, in particular when aiming for group-level fairness. It has been recently shown that a powerful approach to combat spurious correlations is to re-train the last layer on a balanced validation dataset, isolating robust features for the predictor. However, key attributes can sometimes be discarded by neural networks towards the last layer. In this work, we thus consider retraining a classifier on a set of features derived from all layers. We utilize a recently proposed feature selection strategy to select unbiased fea","authors_text":"Eugene Belilovsky, Geraldin Nanfack, Humza Wajid Hameed","cross_cats":["cs.AI"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-09-23T00:31:39Z","title":"Not Only the Last-Layer Features for Spurious Correlations: All Layer Deep Feature Reweighting"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2409.14637","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":"sha256:473af6179c23b8b43d5d2ab0eb1f56cf891432570e435ab43d24160db827dcd5","target":"record","created_at":"2026-07-05T09:10:19Z","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":"5cfaa034503f04a44bf93f2b081ff3fe4cba6f7431209d7ed1675e2668b8fe65","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2024-09-23T00:31:39Z","title_canon_sha256":"339de17aad39a5cf6afc888a1ee880ba2e1197c4406c6f7bd6d0c0337248c343"},"schema_version":"1.0","source":{"id":"2409.14637","kind":"arxiv","version":1}},"canonical_sha256":"34d068ee010d7e6ed31767f76b4657bb5f3a579b915bdd093c4e4482ccc1bdb4","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"34d068ee010d7e6ed31767f76b4657bb5f3a579b915bdd093c4e4482ccc1bdb4","first_computed_at":"2026-07-05T09:10:19.542581Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:10:19.542581Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"rfUZsRJIVjyHebnRbP8M8j4+9TtcfSzKAnGQzW7WOY3OtRCzUj+TabLGgQ5lHj2Vl0/lFwd6Bgt3C1sbyh5ZCQ==","signature_status":"signed_v1","signed_at":"2026-07-05T09:10:19.543107Z","signed_message":"canonical_sha256_bytes"},"source_id":"2409.14637","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:473af6179c23b8b43d5d2ab0eb1f56cf891432570e435ab43d24160db827dcd5","sha256:2263181dc732c2a27413b5f054e585f0e96c66ceab19f67e3e8213932855cdbe"],"state_sha256":"bedaadb824ab120eef611f52e808d391fb4b5a990d52b2c7dbddfb8a7f2e28f5"}