{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:N7AFOMRU5UALOFZ7P5QPL6RXOI","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":"c350b3d165a636e730fd9e6f874b0cc91ef6234da8176f3072b16930c25ef9ca","cross_cats_sorted":["cs.CY"],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CL","submitted_at":"2023-08-08T15:46:27Z","title_canon_sha256":"b7daf8310348214dcdd9e9e73c472029dc3f53a134fdf18cbe9c19cb62dfcd54"},"schema_version":"1.0","source":{"id":"2308.04346","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2308.04346","created_at":"2026-07-05T06:39:26Z"},{"alias_kind":"arxiv_version","alias_value":"2308.04346v1","created_at":"2026-07-05T06:39:26Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2308.04346","created_at":"2026-07-05T06:39:26Z"},{"alias_kind":"pith_short_12","alias_value":"N7AFOMRU5UAL","created_at":"2026-07-05T06:39:26Z"},{"alias_kind":"pith_short_16","alias_value":"N7AFOMRU5UALOFZ7","created_at":"2026-07-05T06:39:26Z"},{"alias_kind":"pith_short_8","alias_value":"N7AFOMRU","created_at":"2026-07-05T06:39:26Z"}],"graph_snapshots":[{"event_id":"sha256:cd707f034326ef8f749e66ee1e9ca291b1bbac34efcd665d23e350cfe2c37e75","target":"graph","created_at":"2026-07-05T06:39:26Z","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/2308.04346/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"We investigate the potential for nationality biases in natural language processing (NLP) models using human evaluation methods. Biased NLP models can perpetuate stereotypes and lead to algorithmic discrimination, posing a significant challenge to the fairness and justice of AI systems. Our study employs a two-step mixed-methods approach that includes both quantitative and qualitative analysis to identify and understand the impact of nationality bias in a text generation model. Through our human-centered quantitative analysis, we measure the extent of nationality bias in articles generated by A","authors_text":"Pranav Narayanan Venkit, Ruchi Panchanadikar, Sanjana Gautam, Shomir Wilson, Ting-Hao `Kenneth' Huang","cross_cats":["cs.CY"],"headline":"","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CL","submitted_at":"2023-08-08T15:46:27Z","title":"Unmasking Nationality Bias: A Study of Human Perception of Nationalities in AI-Generated Articles"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2308.04346","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:a81013b2f274b76867189fb9ccb73a17fd55799ced7155d46c0a1a41465dbb4a","target":"record","created_at":"2026-07-05T06:39:26Z","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":"c350b3d165a636e730fd9e6f874b0cc91ef6234da8176f3072b16930c25ef9ca","cross_cats_sorted":["cs.CY"],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CL","submitted_at":"2023-08-08T15:46:27Z","title_canon_sha256":"b7daf8310348214dcdd9e9e73c472029dc3f53a134fdf18cbe9c19cb62dfcd54"},"schema_version":"1.0","source":{"id":"2308.04346","kind":"arxiv","version":1}},"canonical_sha256":"6fc0573234ed00b7173f7f60f5fa37722b44851d82fd56fb706a6c8a7fca42ea","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"6fc0573234ed00b7173f7f60f5fa37722b44851d82fd56fb706a6c8a7fca42ea","first_computed_at":"2026-07-05T06:39:26.391979Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T06:39:26.391979Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"kxnbOZYaaS+U7rxhUD3j/ivJUEfp9ZTkLIaR1FoPjVXohLL8Lfq9vK0xIrj/+3kWafgiM2FxbXkrBxNrRTMSBg==","signature_status":"signed_v1","signed_at":"2026-07-05T06:39:26.392424Z","signed_message":"canonical_sha256_bytes"},"source_id":"2308.04346","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:a81013b2f274b76867189fb9ccb73a17fd55799ced7155d46c0a1a41465dbb4a","sha256:cd707f034326ef8f749e66ee1e9ca291b1bbac34efcd665d23e350cfe2c37e75"],"state_sha256":"2cc476cd2ce86b5973a34dfcb2a7f02825d84d798a39b5e9563360c61badef5a"}