{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:LIB77WLD2PFMIKF2U5SM6I7YUF","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":"1ef56fe2be239504e4cd609de758f8586d5ca4b2f6b8890cb5701911ce97908e","cross_cats_sorted":["cs.AI","stat.ML"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2022-10-11T08:26:19Z","title_canon_sha256":"48cd72e56dea23fd445daaa80ef747c829f98d7612e2c9ce66d02bc87c1f8b4c"},"schema_version":"1.0","source":{"id":"2210.05248","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2210.05248","created_at":"2026-07-05T06:58:36Z"},{"alias_kind":"arxiv_version","alias_value":"2210.05248v2","created_at":"2026-07-05T06:58:36Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2210.05248","created_at":"2026-07-05T06:58:36Z"},{"alias_kind":"pith_short_12","alias_value":"LIB77WLD2PFM","created_at":"2026-07-05T06:58:36Z"},{"alias_kind":"pith_short_16","alias_value":"LIB77WLD2PFMIKF2","created_at":"2026-07-05T06:58:36Z"},{"alias_kind":"pith_short_8","alias_value":"LIB77WLD","created_at":"2026-07-05T06:58:36Z"}],"graph_snapshots":[{"event_id":"sha256:5e1eaa18bb33d4c75181322b79ab37bb9d0a771ffa62d4abec378152ab67b806","target":"graph","created_at":"2026-07-05T06:58:36Z","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/2210.05248/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Spurious correlations can cause strong biases in deep neural networks, impairing generalization ability. While most existing debiasing methods require full supervision on either spurious attributes or target labels, training a debiased model from a limited amount of both annotations is still an open question. To address this issue, we investigate an interesting phenomenon using the spectral analysis of latent representations: spuriously correlated attributes make neural networks inductively biased towards encoding lower effective rank representations. We also show that a rank regularization ca","authors_text":"Chanyong Jung, Geon Yeong Park, Jong Chul Ye, Sangmin Lee, Sang Wan Lee","cross_cats":["cs.AI","stat.ML"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2022-10-11T08:26:19Z","title":"Self-supervised debiasing using low rank regularization"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2210.05248","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":"sha256:42ac2f8dfbe3fb06fc3d3fbe003f753a2ecf9296ae4cb18768e197b4a3f4c01c","target":"record","created_at":"2026-07-05T06:58:36Z","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":"1ef56fe2be239504e4cd609de758f8586d5ca4b2f6b8890cb5701911ce97908e","cross_cats_sorted":["cs.AI","stat.ML"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2022-10-11T08:26:19Z","title_canon_sha256":"48cd72e56dea23fd445daaa80ef747c829f98d7612e2c9ce66d02bc87c1f8b4c"},"schema_version":"1.0","source":{"id":"2210.05248","kind":"arxiv","version":2}},"canonical_sha256":"5a03ffd963d3cac428baa764cf23f8a169b7a77f958e4fa4ca04ec6c48be230c","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"5a03ffd963d3cac428baa764cf23f8a169b7a77f958e4fa4ca04ec6c48be230c","first_computed_at":"2026-07-05T06:58:36.427993Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T06:58:36.427993Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"5o5mKMqqdKMpu4uZ6fNAD9NFY5fEFFM4xtvC+njP/k05mhH1Xdz5ECeeBPBMskl1CiJUlXjCOAWTzx6mHf8BAA==","signature_status":"signed_v1","signed_at":"2026-07-05T06:58:36.428548Z","signed_message":"canonical_sha256_bytes"},"source_id":"2210.05248","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:42ac2f8dfbe3fb06fc3d3fbe003f753a2ecf9296ae4cb18768e197b4a3f4c01c","sha256:5e1eaa18bb33d4c75181322b79ab37bb9d0a771ffa62d4abec378152ab67b806"],"state_sha256":"75f16fb278db686bfde9dfc2e7e27ffbf479dd3f90aa9c4d584bcf149a03b67d"}