{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:FZM4LLOVNFBBSFVX56BT47VUQS","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":"d491df57f44088e56b9feef97d8bcfc7640c447a3c1e13661bbd6a1f9d9bb7bf","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2023-05-18T18:15:07Z","title_canon_sha256":"a9b8634642b2dd2b155f277f23c51141f2ed6e22d216537f5c11b0c4cda43204"},"schema_version":"1.0","source":{"id":"2305.11242","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2305.11242","created_at":"2026-07-05T06:11:34Z"},{"alias_kind":"arxiv_version","alias_value":"2305.11242v1","created_at":"2026-07-05T06:11:34Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2305.11242","created_at":"2026-07-05T06:11:34Z"},{"alias_kind":"pith_short_12","alias_value":"FZM4LLOVNFBB","created_at":"2026-07-05T06:11:34Z"},{"alias_kind":"pith_short_16","alias_value":"FZM4LLOVNFBBSFVX","created_at":"2026-07-05T06:11:34Z"},{"alias_kind":"pith_short_8","alias_value":"FZM4LLOV","created_at":"2026-07-05T06:11:34Z"}],"graph_snapshots":[{"event_id":"sha256:6fd994c47b83f9bc91ec27003be4f45f296e782db260a2a71115f376910912c5","target":"graph","created_at":"2026-07-05T06:11:34Z","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/2305.11242/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Studies in bias and fairness in natural language processing have primarily examined social biases within a single language and/or across few attributes (e.g. gender, race). However, biases can manifest differently across various languages for individual attributes. As a result, it is critical to examine biases within each language and attribute. Of equal importance is to study how these biases compare across languages and how the biases are affected when training a model on multilingual data versus monolingual data. We present a bias analysis across Italian, Chinese, English, Hebrew, and Spani","authors_text":"Dan Roth, Jie Ma, Ling Liu, Miguel Ballesteros, Neha Anna John, Sharon Levy, Vittorio Castelli, Yogarshi Vyas, Yoshinari Fujinuma","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2023-05-18T18:15:07Z","title":"Comparing Biases and the Impact of Multilingual Training across Multiple Languages"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2305.11242","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":"sha256:1d8ada2a56b722014432ca5b8332c6afea94878902c4fa1b47257557fb5a7392","target":"record","created_at":"2026-07-05T06:11:34Z","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":"d491df57f44088e56b9feef97d8bcfc7640c447a3c1e13661bbd6a1f9d9bb7bf","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2023-05-18T18:15:07Z","title_canon_sha256":"a9b8634642b2dd2b155f277f23c51141f2ed6e22d216537f5c11b0c4cda43204"},"schema_version":"1.0","source":{"id":"2305.11242","kind":"arxiv","version":1}},"canonical_sha256":"2e59c5add569421916b7ef833e7eb4849ac80c5b23cd693c234145fd2437b413","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"2e59c5add569421916b7ef833e7eb4849ac80c5b23cd693c234145fd2437b413","first_computed_at":"2026-07-05T06:11:34.775534Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T06:11:34.775534Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"nxcolQSkiYPXfJ7CQFngpj4vHDLdWApuCm+8Asx7UcFKpmvbaugpKltktHorLyEMU3JklQcs3cYJw20kXfgXBg==","signature_status":"signed_v1","signed_at":"2026-07-05T06:11:34.776024Z","signed_message":"canonical_sha256_bytes"},"source_id":"2305.11242","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:1d8ada2a56b722014432ca5b8332c6afea94878902c4fa1b47257557fb5a7392","sha256:6fd994c47b83f9bc91ec27003be4f45f296e782db260a2a71115f376910912c5"],"state_sha256":"7ac7dd8acfe308a2da47773842b4339beecec120e45ea2cbc5cdc08314aa0272"}