{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:OFCFXBRYHUVPUSH5X7R2HQDWEW","short_pith_number":"pith:OFCFXBRY","canonical_record":{"source":{"id":"2410.10489","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-10-14T13:33:00Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"f00cab04d9be37e69b0637427a64322ba7688a6baf4566aed2d6c68dc880e10d","abstract_canon_sha256":"62350ea600920db3cd9455f516f34a9534116a08a8bc41dc015f1fe4e5fd558f"},"schema_version":"1.0"},"canonical_sha256":"71445b86383d2afa48fdbfe3a3c076258d6a2116d602e883ac6e3f30bf91476a","source":{"kind":"arxiv","id":"2410.10489","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2410.10489","created_at":"2026-07-05T09:20:17Z"},{"alias_kind":"arxiv_version","alias_value":"2410.10489v1","created_at":"2026-07-05T09:20:17Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2410.10489","created_at":"2026-07-05T09:20:17Z"},{"alias_kind":"pith_short_12","alias_value":"OFCFXBRYHUVP","created_at":"2026-07-05T09:20:17Z"},{"alias_kind":"pith_short_16","alias_value":"OFCFXBRYHUVPUSH5","created_at":"2026-07-05T09:20:17Z"},{"alias_kind":"pith_short_8","alias_value":"OFCFXBRY","created_at":"2026-07-05T09:20:17Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:OFCFXBRYHUVPUSH5X7R2HQDWEW","target":"record","payload":{"canonical_record":{"source":{"id":"2410.10489","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-10-14T13:33:00Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"f00cab04d9be37e69b0637427a64322ba7688a6baf4566aed2d6c68dc880e10d","abstract_canon_sha256":"62350ea600920db3cd9455f516f34a9534116a08a8bc41dc015f1fe4e5fd558f"},"schema_version":"1.0"},"canonical_sha256":"71445b86383d2afa48fdbfe3a3c076258d6a2116d602e883ac6e3f30bf91476a","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:20:17.064426Z","signature_b64":"uAnAxJuHVxSG+0JGctcn30DJWvhLLrfddq7MC5pt6Pdr0h9AK0KeQI3vaoSsYxq6DsLqIy9P5pXJdNBJMgGeBA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"71445b86383d2afa48fdbfe3a3c076258d6a2116d602e883ac6e3f30bf91476a","last_reissued_at":"2026-07-05T09:20:17.063978Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:20:17.063978Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2410.10489","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":"2026-07-05T09:20:17Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"YI+RUevk3DGamAO/rYe0m7qQHE4b/bbWWKWHxgbgkG2TeRg6HStU8MDb06p2eBnGizeebz5sICYLTKUyKbZiAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-16T04:08:32.042811Z"},"content_sha256":"13cb39434710ef0b119047bdd89eb1244ebb20f4397813b2863dc71f8dd85bf8","schema_version":"1.0","event_id":"sha256:13cb39434710ef0b119047bdd89eb1244ebb20f4397813b2863dc71f8dd85bf8"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:OFCFXBRYHUVPUSH5X7R2HQDWEW","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Cultural Fidelity in Large-Language Models: An Evaluation of Online Language Resources as a Driver of Model Performance in Value Representation","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CL","authors_text":"Caroline Ida Kuria, Estelle Pan, Gloria Gerhardt, Jonty Katz, Sharif Kazemi, Umang Prabhakar","submitted_at":"2024-10-14T13:33:00Z","abstract_excerpt":"The training data for LLMs embeds societal values, increasing their familiarity with the language's culture. Our analysis found that 44% of the variance in the ability of GPT-4o to reflect the societal values of a country, as measured by the World Values Survey, correlates with the availability of digital resources in that language. Notably, the error rate was more than five times higher for the languages of the lowest resource compared to the languages of the highest resource. For GPT-4-turbo, this correlation rose to 72%, suggesting efforts to improve the familiarity with the non-English lan"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2410.10489","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/2410.10489/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":"2026-07-05T09:20:17Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"rM2PhfOVHqfX8TvEHRaPjfpL61JD8PrMk+G/8arr9WKk7pwTcZw45Btqk35hUbeFyV+t+jqxgeYMZBWC2khACw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-16T04:08:32.043308Z"},"content_sha256":"8421c16c177caeb55430ea93bae8ed1e7d26e76e07a6a90f73c815a4799a5e65","schema_version":"1.0","event_id":"sha256:8421c16c177caeb55430ea93bae8ed1e7d26e76e07a6a90f73c815a4799a5e65"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/OFCFXBRYHUVPUSH5X7R2HQDWEW/bundle.json","state_url":"https://pith.science/pith/OFCFXBRYHUVPUSH5X7R2HQDWEW/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/OFCFXBRYHUVPUSH5X7R2HQDWEW/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":"2026-08-16T04:08:32Z","links":{"resolver":"https://pith.science/pith/OFCFXBRYHUVPUSH5X7R2HQDWEW","bundle":"https://pith.science/pith/OFCFXBRYHUVPUSH5X7R2HQDWEW/bundle.json","state":"https://pith.science/pith/OFCFXBRYHUVPUSH5X7R2HQDWEW/state.json","well_known_bundle":"https://pith.science/.well-known/pith/OFCFXBRYHUVPUSH5X7R2HQDWEW/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:OFCFXBRYHUVPUSH5X7R2HQDWEW","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":"62350ea600920db3cd9455f516f34a9534116a08a8bc41dc015f1fe4e5fd558f","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-10-14T13:33:00Z","title_canon_sha256":"f00cab04d9be37e69b0637427a64322ba7688a6baf4566aed2d6c68dc880e10d"},"schema_version":"1.0","source":{"id":"2410.10489","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2410.10489","created_at":"2026-07-05T09:20:17Z"},{"alias_kind":"arxiv_version","alias_value":"2410.10489v1","created_at":"2026-07-05T09:20:17Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2410.10489","created_at":"2026-07-05T09:20:17Z"},{"alias_kind":"pith_short_12","alias_value":"OFCFXBRYHUVP","created_at":"2026-07-05T09:20:17Z"},{"alias_kind":"pith_short_16","alias_value":"OFCFXBRYHUVPUSH5","created_at":"2026-07-05T09:20:17Z"},{"alias_kind":"pith_short_8","alias_value":"OFCFXBRY","created_at":"2026-07-05T09:20:17Z"}],"graph_snapshots":[{"event_id":"sha256:8421c16c177caeb55430ea93bae8ed1e7d26e76e07a6a90f73c815a4799a5e65","target":"graph","created_at":"2026-07-05T09:20:17Z","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/2410.10489/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"The training data for LLMs embeds societal values, increasing their familiarity with the language's culture. Our analysis found that 44% of the variance in the ability of GPT-4o to reflect the societal values of a country, as measured by the World Values Survey, correlates with the availability of digital resources in that language. Notably, the error rate was more than five times higher for the languages of the lowest resource compared to the languages of the highest resource. For GPT-4-turbo, this correlation rose to 72%, suggesting efforts to improve the familiarity with the non-English lan","authors_text":"Caroline Ida Kuria, Estelle Pan, Gloria Gerhardt, Jonty Katz, Sharif Kazemi, Umang Prabhakar","cross_cats":["cs.AI"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-10-14T13:33:00Z","title":"Cultural Fidelity in Large-Language Models: An Evaluation of Online Language Resources as a Driver of Model Performance in Value Representation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2410.10489","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":"sha256:13cb39434710ef0b119047bdd89eb1244ebb20f4397813b2863dc71f8dd85bf8","target":"record","created_at":"2026-07-05T09:20:17Z","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":"62350ea600920db3cd9455f516f34a9534116a08a8bc41dc015f1fe4e5fd558f","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-10-14T13:33:00Z","title_canon_sha256":"f00cab04d9be37e69b0637427a64322ba7688a6baf4566aed2d6c68dc880e10d"},"schema_version":"1.0","source":{"id":"2410.10489","kind":"arxiv","version":1}},"canonical_sha256":"71445b86383d2afa48fdbfe3a3c076258d6a2116d602e883ac6e3f30bf91476a","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"71445b86383d2afa48fdbfe3a3c076258d6a2116d602e883ac6e3f30bf91476a","first_computed_at":"2026-07-05T09:20:17.063978Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:20:17.063978Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"uAnAxJuHVxSG+0JGctcn30DJWvhLLrfddq7MC5pt6Pdr0h9AK0KeQI3vaoSsYxq6DsLqIy9P5pXJdNBJMgGeBA==","signature_status":"signed_v1","signed_at":"2026-07-05T09:20:17.064426Z","signed_message":"canonical_sha256_bytes"},"source_id":"2410.10489","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:13cb39434710ef0b119047bdd89eb1244ebb20f4397813b2863dc71f8dd85bf8","sha256:8421c16c177caeb55430ea93bae8ed1e7d26e76e07a6a90f73c815a4799a5e65"],"state_sha256":"6e9bd8431e5fd8e7e8e5d49708434de73f70ec1cdcac6e0267a661ea2230f2ff"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"t8CCX37iAsArFA0ioI4sooESXoojGoP9BtNVL66ZRuOAoUviXnmTlEqJOGPQWxsmzOG0lUXW3mazIKk/qnjdCw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-16T04:08:32.046770Z","bundle_sha256":"52060ca975660679b5c6a0ccb810a4b6332e8f795a7dc399bd189c122d16f0fc"}}