{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:GMKYCPGOXOITJY6IUHW5HBFSV7","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":"6b22e245abb10bb7013289465db3b2b561589df901e2f9a083e84456fd8a9b42","cross_cats_sorted":["cs.AI","cs.CL"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CY","submitted_at":"2025-08-22T08:13:28Z","title_canon_sha256":"84298f1bfd4a7e7ee5d77e04910a87914709b457a4989bcf3d297f34c4d38c52"},"schema_version":"1.0","source":{"id":"2508.19269","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2508.19269","created_at":"2026-07-05T11:59:42Z"},{"alias_kind":"arxiv_version","alias_value":"2508.19269v1","created_at":"2026-07-05T11:59:42Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2508.19269","created_at":"2026-07-05T11:59:42Z"},{"alias_kind":"pith_short_12","alias_value":"GMKYCPGOXOIT","created_at":"2026-07-05T11:59:42Z"},{"alias_kind":"pith_short_16","alias_value":"GMKYCPGOXOITJY6I","created_at":"2026-07-05T11:59:42Z"},{"alias_kind":"pith_short_8","alias_value":"GMKYCPGO","created_at":"2026-07-05T11:59:42Z"}],"graph_snapshots":[{"event_id":"sha256:c829001205f21752f60dc3bf962ac1e1642f97dff37d41f0a877dda90e2d382c","target":"graph","created_at":"2026-07-05T11:59:42Z","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/2508.19269/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Large language models (LLMs) are often trained on data that reflect WEIRD values: Western, Educated, Industrialized, Rich, and Democratic. This raises concerns about cultural bias and fairness. Using responses to the World Values Survey, we evaluated five widely used LLMs: GPT-3.5, GPT-4, Llama-3, BLOOM, and Qwen. We measured how closely these responses aligned with the values of the WEIRD countries and whether they conflicted with human rights principles. To reflect global diversity, we compared the results with the Universal Declaration of Human Rights and three regional charters from Asia, ","authors_text":"Daniele Quercia, Ke Zhou, Marios Constantinides","cross_cats":["cs.AI","cs.CL"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CY","submitted_at":"2025-08-22T08:13:28Z","title":"Should LLMs be WEIRD? Exploring WEIRDness and Human Rights in Large Language Models"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2508.19269","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:dac297f441f1340931b8cf197adb4c3a15ca7d8316fb3f45825fa5b43c4fdb3b","target":"record","created_at":"2026-07-05T11:59:42Z","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":"6b22e245abb10bb7013289465db3b2b561589df901e2f9a083e84456fd8a9b42","cross_cats_sorted":["cs.AI","cs.CL"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CY","submitted_at":"2025-08-22T08:13:28Z","title_canon_sha256":"84298f1bfd4a7e7ee5d77e04910a87914709b457a4989bcf3d297f34c4d38c52"},"schema_version":"1.0","source":{"id":"2508.19269","kind":"arxiv","version":1}},"canonical_sha256":"3315813ccebb9134e3c8a1edd384b2afec4a914662f4adb68319e291152ea412","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"3315813ccebb9134e3c8a1edd384b2afec4a914662f4adb68319e291152ea412","first_computed_at":"2026-07-05T11:59:42.047172Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:59:42.047172Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Bek/E4Q0CNGQJop6dnEsKyqAFueN2F7wZtrZy0DcLS6ZA8eOm22rY6gS+bZk298uoO6eiJrvuc4OM0729pPoCQ==","signature_status":"signed_v1","signed_at":"2026-07-05T11:59:42.047653Z","signed_message":"canonical_sha256_bytes"},"source_id":"2508.19269","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:dac297f441f1340931b8cf197adb4c3a15ca7d8316fb3f45825fa5b43c4fdb3b","sha256:c829001205f21752f60dc3bf962ac1e1642f97dff37d41f0a877dda90e2d382c"],"state_sha256":"dbacbe8e395e93fd2a3def0ff108df921ae28561e4e3bdd3f99f6700643ea5d1"}