{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2021:3C3SX4FGIB6LKHDFIMULCHKH3Y","short_pith_number":"pith:3C3SX4FG","canonical_record":{"source":{"id":"2109.04095","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2021-09-09T08:28:22Z","cross_cats_sorted":[],"title_canon_sha256":"d2f78e6a5f6825bd232e39c1fba9be547781ab07c44f03aadfbfb618f694a386","abstract_canon_sha256":"99198cb1316005d767e3cb91db0d0fff24a82d9eb28cad90c611ff4ef5bf51cf"},"schema_version":"1.0"},"canonical_sha256":"d8b72bf0a6407cb51c654328b11d47de1c4b1b94bd8191eaf27f516ad1b71d15","source":{"kind":"arxiv","id":"2109.04095","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2109.04095","created_at":"2026-07-05T03:12:54Z"},{"alias_kind":"arxiv_version","alias_value":"2109.04095v1","created_at":"2026-07-05T03:12:54Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2109.04095","created_at":"2026-07-05T03:12:54Z"},{"alias_kind":"pith_short_12","alias_value":"3C3SX4FGIB6L","created_at":"2026-07-05T03:12:54Z"},{"alias_kind":"pith_short_16","alias_value":"3C3SX4FGIB6LKHDF","created_at":"2026-07-05T03:12:54Z"},{"alias_kind":"pith_short_8","alias_value":"3C3SX4FG","created_at":"2026-07-05T03:12:54Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2021:3C3SX4FGIB6LKHDFIMULCHKH3Y","target":"record","payload":{"canonical_record":{"source":{"id":"2109.04095","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2021-09-09T08:28:22Z","cross_cats_sorted":[],"title_canon_sha256":"d2f78e6a5f6825bd232e39c1fba9be547781ab07c44f03aadfbfb618f694a386","abstract_canon_sha256":"99198cb1316005d767e3cb91db0d0fff24a82d9eb28cad90c611ff4ef5bf51cf"},"schema_version":"1.0"},"canonical_sha256":"d8b72bf0a6407cb51c654328b11d47de1c4b1b94bd8191eaf27f516ad1b71d15","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T03:12:54.825455Z","signature_b64":"VrE2viiU2MaWvEwd35zQQaS3f35ytsyDH5ueMjWmY8qKlV4ygzcKXTrkHQVy+jcfoR3xiIU5b6Hc9eDkRXdHDA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"d8b72bf0a6407cb51c654328b11d47de1c4b1b94bd8191eaf27f516ad1b71d15","last_reissued_at":"2026-07-05T03:12:54.825037Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T03:12:54.825037Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2109.04095","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":"2026-07-05T03:12:54Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"oALHfjy3Sk06DZUsW7h+tfGFmA4tyxiMD886p7Nv1jsauFFUiAse41PSOipfOEMB9r25N6FTkPaNj63fqtZnAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-24T08:11:30.128333Z"},"content_sha256":"067e4982017b27111dca5040ca6b5da99819e5c4d3a2b6cab71e7a885bf31b4e","schema_version":"1.0","event_id":"sha256:067e4982017b27111dca5040ca6b5da99819e5c4d3a2b6cab71e7a885bf31b4e"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2021:3C3SX4FGIB6LKHDFIMULCHKH3Y","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Debiasing Methods in Natural Language Understanding Make Bias More Accessible","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Michael Mendelson, Yonatan Belinkov","submitted_at":"2021-09-09T08:28:22Z","abstract_excerpt":"Model robustness to bias is often determined by the generalization on carefully designed out-of-distribution datasets. Recent debiasing methods in natural language understanding (NLU) improve performance on such datasets by pressuring models into making unbiased predictions. An underlying assumption behind such methods is that this also leads to the discovery of more robust features in the model's inner representations. We propose a general probing-based framework that allows for post-hoc interpretation of biases in language models, and use an information-theoretic approach to measure the extr"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2109.04095","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/2109.04095/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":"2026-07-05T03:12:54Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"TQD6eRWNy/ia/Bp75PXoGZPbscjsD/qgZkrHOc1iA4Qh/0Tn6ZeCdtpzBKpGaPnTpACBMAwlYxgWnd3zbH3VCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-24T08:11:30.128714Z"},"content_sha256":"17de6a9e7bb606cb2792949475d70283dfa5c306f6a642e3705bc8565933f1f9","schema_version":"1.0","event_id":"sha256:17de6a9e7bb606cb2792949475d70283dfa5c306f6a642e3705bc8565933f1f9"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/3C3SX4FGIB6LKHDFIMULCHKH3Y/bundle.json","state_url":"https://pith.science/pith/3C3SX4FGIB6LKHDFIMULCHKH3Y/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/3C3SX4FGIB6LKHDFIMULCHKH3Y/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":"2026-07-24T08:11:30Z","links":{"resolver":"https://pith.science/pith/3C3SX4FGIB6LKHDFIMULCHKH3Y","bundle":"https://pith.science/pith/3C3SX4FGIB6LKHDFIMULCHKH3Y/bundle.json","state":"https://pith.science/pith/3C3SX4FGIB6LKHDFIMULCHKH3Y/state.json","well_known_bundle":"https://pith.science/.well-known/pith/3C3SX4FGIB6LKHDFIMULCHKH3Y/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2021:3C3SX4FGIB6LKHDFIMULCHKH3Y","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":"99198cb1316005d767e3cb91db0d0fff24a82d9eb28cad90c611ff4ef5bf51cf","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2021-09-09T08:28:22Z","title_canon_sha256":"d2f78e6a5f6825bd232e39c1fba9be547781ab07c44f03aadfbfb618f694a386"},"schema_version":"1.0","source":{"id":"2109.04095","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2109.04095","created_at":"2026-07-05T03:12:54Z"},{"alias_kind":"arxiv_version","alias_value":"2109.04095v1","created_at":"2026-07-05T03:12:54Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2109.04095","created_at":"2026-07-05T03:12:54Z"},{"alias_kind":"pith_short_12","alias_value":"3C3SX4FGIB6L","created_at":"2026-07-05T03:12:54Z"},{"alias_kind":"pith_short_16","alias_value":"3C3SX4FGIB6LKHDF","created_at":"2026-07-05T03:12:54Z"},{"alias_kind":"pith_short_8","alias_value":"3C3SX4FG","created_at":"2026-07-05T03:12:54Z"}],"graph_snapshots":[{"event_id":"sha256:17de6a9e7bb606cb2792949475d70283dfa5c306f6a642e3705bc8565933f1f9","target":"graph","created_at":"2026-07-05T03:12:54Z","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/2109.04095/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Model robustness to bias is often determined by the generalization on carefully designed out-of-distribution datasets. Recent debiasing methods in natural language understanding (NLU) improve performance on such datasets by pressuring models into making unbiased predictions. An underlying assumption behind such methods is that this also leads to the discovery of more robust features in the model's inner representations. We propose a general probing-based framework that allows for post-hoc interpretation of biases in language models, and use an information-theoretic approach to measure the extr","authors_text":"Michael Mendelson, Yonatan Belinkov","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2021-09-09T08:28:22Z","title":"Debiasing Methods in Natural Language Understanding Make Bias More Accessible"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2109.04095","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":"sha256:067e4982017b27111dca5040ca6b5da99819e5c4d3a2b6cab71e7a885bf31b4e","target":"record","created_at":"2026-07-05T03:12:54Z","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":"99198cb1316005d767e3cb91db0d0fff24a82d9eb28cad90c611ff4ef5bf51cf","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2021-09-09T08:28:22Z","title_canon_sha256":"d2f78e6a5f6825bd232e39c1fba9be547781ab07c44f03aadfbfb618f694a386"},"schema_version":"1.0","source":{"id":"2109.04095","kind":"arxiv","version":1}},"canonical_sha256":"d8b72bf0a6407cb51c654328b11d47de1c4b1b94bd8191eaf27f516ad1b71d15","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"d8b72bf0a6407cb51c654328b11d47de1c4b1b94bd8191eaf27f516ad1b71d15","first_computed_at":"2026-07-05T03:12:54.825037Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T03:12:54.825037Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"VrE2viiU2MaWvEwd35zQQaS3f35ytsyDH5ueMjWmY8qKlV4ygzcKXTrkHQVy+jcfoR3xiIU5b6Hc9eDkRXdHDA==","signature_status":"signed_v1","signed_at":"2026-07-05T03:12:54.825455Z","signed_message":"canonical_sha256_bytes"},"source_id":"2109.04095","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:067e4982017b27111dca5040ca6b5da99819e5c4d3a2b6cab71e7a885bf31b4e","sha256:17de6a9e7bb606cb2792949475d70283dfa5c306f6a642e3705bc8565933f1f9"],"state_sha256":"d2a3756b6c6c9b0d8e1dc1f430571f66553c5643fbb5bb9d010bae7b2914c9ad"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"9IwZp3KUjGQjrWRZUPRyiCdLRF0U5WTsCYlhdK/K/nMV/p+6H5eQALfhfWWkVVLYidZfCikLu5Zw9XXaxnmFAg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-24T08:11:30.131252Z","bundle_sha256":"ab87a5c074fd102cfd15daf9b438e6872470c687939b7fad5f8d7c19de5a710d"}}