{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:AB2TCK47BEQ2UUDP2PYE5NXLZW","short_pith_number":"pith:AB2TCK47","canonical_record":{"source":{"id":"2406.07243","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-06-11T13:23:14Z","cross_cats_sorted":[],"title_canon_sha256":"740bf31712b351d17c45547c7dc3cdab4ac0a74739d42bc8591c1473e16a832b","abstract_canon_sha256":"625dd895186dee82770cb402ef633255bfef2801680740bcf6ec71613482b68d"},"schema_version":"1.0"},"canonical_sha256":"0075312b9f0921aa506fd3f04eb6ebcdaa4d6e93c7916ad93e6bbbf643288304","source":{"kind":"arxiv","id":"2406.07243","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2406.07243","created_at":"2026-07-05T08:44:55Z"},{"alias_kind":"arxiv_version","alias_value":"2406.07243v3","created_at":"2026-07-05T08:44:55Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2406.07243","created_at":"2026-07-05T08:44:55Z"},{"alias_kind":"pith_short_12","alias_value":"AB2TCK47BEQ2","created_at":"2026-07-05T08:44:55Z"},{"alias_kind":"pith_short_16","alias_value":"AB2TCK47BEQ2UUDP","created_at":"2026-07-05T08:44:55Z"},{"alias_kind":"pith_short_8","alias_value":"AB2TCK47","created_at":"2026-07-05T08:44:55Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:AB2TCK47BEQ2UUDP2PYE5NXLZW","target":"record","payload":{"canonical_record":{"source":{"id":"2406.07243","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-06-11T13:23:14Z","cross_cats_sorted":[],"title_canon_sha256":"740bf31712b351d17c45547c7dc3cdab4ac0a74739d42bc8591c1473e16a832b","abstract_canon_sha256":"625dd895186dee82770cb402ef633255bfef2801680740bcf6ec71613482b68d"},"schema_version":"1.0"},"canonical_sha256":"0075312b9f0921aa506fd3f04eb6ebcdaa4d6e93c7916ad93e6bbbf643288304","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T08:44:55.084571Z","signature_b64":"jAhEaIFXmLOF0CyIl3gPzvZ8WlWB9lHHlGlLCQd9LhuqD51UfeVUJ+7ZsNuEWQW4DWPRAI+9nxfMapumvFLTAQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"0075312b9f0921aa506fd3f04eb6ebcdaa4d6e93c7916ad93e6bbbf643288304","last_reissued_at":"2026-07-05T08:44:55.084143Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T08:44:55.084143Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2406.07243","source_version":3,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T08:44:55Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"xTFkA17lQey8NbWGFvlNRpf6mXBlJ4cNnbQwDvxOdSTflIlNMYvJIqxtMgonU7bG7eF+NfhFxTOT5gKB6CT5Bg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-03T11:18:14.834509Z"},"content_sha256":"626c525a9417135b5b62fcce3df19f3bef12cdab0a4baab690834ffe809ca4bb","schema_version":"1.0","event_id":"sha256:626c525a9417135b5b62fcce3df19f3bef12cdab0a4baab690834ffe809ca4bb"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:AB2TCK47BEQ2UUDP2PYE5NXLZW","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"MBBQ: A Dataset for Cross-Lingual Comparison of Stereotypes in Generative LLMs","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.CL","authors_text":"Arianna Bisazza, Raquel Fern\\'andez, Vera Neplenbroek","submitted_at":"2024-06-11T13:23:14Z","abstract_excerpt":"Generative large language models (LLMs) have been shown to exhibit harmful biases and stereotypes. While safety fine-tuning typically takes place in English, if at all, these models are being used by speakers of many different languages. There is existing evidence that the performance of these models is inconsistent across languages and that they discriminate based on demographic factors of the user. Motivated by this, we investigate whether the social stereotypes exhibited by LLMs differ as a function of the language used to prompt them, while controlling for cultural differences and task acc"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2406.07243","kind":"arxiv","version":3},"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/2406.07243/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":"2026-07-05T08:44:55Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"pnS9BErBQLKlhsC5VUSl9uKQ3GFVvVqsduX8y06zNvzIrLuuBjkJI+2FwZxB3/w/DkxvtYexrYozqMg6DyV5BA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-03T11:18:14.837421Z"},"content_sha256":"ad1b59cd0ac69aae81cf7ea39a9c391b47b27ed07b51b98dc847a7ae6a1462a2","schema_version":"1.0","event_id":"sha256:ad1b59cd0ac69aae81cf7ea39a9c391b47b27ed07b51b98dc847a7ae6a1462a2"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/AB2TCK47BEQ2UUDP2PYE5NXLZW/bundle.json","state_url":"https://pith.science/pith/AB2TCK47BEQ2UUDP2PYE5NXLZW/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/AB2TCK47BEQ2UUDP2PYE5NXLZW/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":"2026-08-03T11:18:14Z","links":{"resolver":"https://pith.science/pith/AB2TCK47BEQ2UUDP2PYE5NXLZW","bundle":"https://pith.science/pith/AB2TCK47BEQ2UUDP2PYE5NXLZW/bundle.json","state":"https://pith.science/pith/AB2TCK47BEQ2UUDP2PYE5NXLZW/state.json","well_known_bundle":"https://pith.science/.well-known/pith/AB2TCK47BEQ2UUDP2PYE5NXLZW/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:AB2TCK47BEQ2UUDP2PYE5NXLZW","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":"625dd895186dee82770cb402ef633255bfef2801680740bcf6ec71613482b68d","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-06-11T13:23:14Z","title_canon_sha256":"740bf31712b351d17c45547c7dc3cdab4ac0a74739d42bc8591c1473e16a832b"},"schema_version":"1.0","source":{"id":"2406.07243","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2406.07243","created_at":"2026-07-05T08:44:55Z"},{"alias_kind":"arxiv_version","alias_value":"2406.07243v3","created_at":"2026-07-05T08:44:55Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2406.07243","created_at":"2026-07-05T08:44:55Z"},{"alias_kind":"pith_short_12","alias_value":"AB2TCK47BEQ2","created_at":"2026-07-05T08:44:55Z"},{"alias_kind":"pith_short_16","alias_value":"AB2TCK47BEQ2UUDP","created_at":"2026-07-05T08:44:55Z"},{"alias_kind":"pith_short_8","alias_value":"AB2TCK47","created_at":"2026-07-05T08:44:55Z"}],"graph_snapshots":[{"event_id":"sha256:ad1b59cd0ac69aae81cf7ea39a9c391b47b27ed07b51b98dc847a7ae6a1462a2","target":"graph","created_at":"2026-07-05T08:44:55Z","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/2406.07243/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Generative large language models (LLMs) have been shown to exhibit harmful biases and stereotypes. While safety fine-tuning typically takes place in English, if at all, these models are being used by speakers of many different languages. There is existing evidence that the performance of these models is inconsistent across languages and that they discriminate based on demographic factors of the user. Motivated by this, we investigate whether the social stereotypes exhibited by LLMs differ as a function of the language used to prompt them, while controlling for cultural differences and task acc","authors_text":"Arianna Bisazza, Raquel Fern\\'andez, Vera Neplenbroek","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-06-11T13:23:14Z","title":"MBBQ: A Dataset for Cross-Lingual Comparison of Stereotypes in Generative LLMs"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2406.07243","kind":"arxiv","version":3},"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":"sha256:626c525a9417135b5b62fcce3df19f3bef12cdab0a4baab690834ffe809ca4bb","target":"record","created_at":"2026-07-05T08:44:55Z","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":"625dd895186dee82770cb402ef633255bfef2801680740bcf6ec71613482b68d","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-06-11T13:23:14Z","title_canon_sha256":"740bf31712b351d17c45547c7dc3cdab4ac0a74739d42bc8591c1473e16a832b"},"schema_version":"1.0","source":{"id":"2406.07243","kind":"arxiv","version":3}},"canonical_sha256":"0075312b9f0921aa506fd3f04eb6ebcdaa4d6e93c7916ad93e6bbbf643288304","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"0075312b9f0921aa506fd3f04eb6ebcdaa4d6e93c7916ad93e6bbbf643288304","first_computed_at":"2026-07-05T08:44:55.084143Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T08:44:55.084143Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"jAhEaIFXmLOF0CyIl3gPzvZ8WlWB9lHHlGlLCQd9LhuqD51UfeVUJ+7ZsNuEWQW4DWPRAI+9nxfMapumvFLTAQ==","signature_status":"signed_v1","signed_at":"2026-07-05T08:44:55.084571Z","signed_message":"canonical_sha256_bytes"},"source_id":"2406.07243","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:626c525a9417135b5b62fcce3df19f3bef12cdab0a4baab690834ffe809ca4bb","sha256:ad1b59cd0ac69aae81cf7ea39a9c391b47b27ed07b51b98dc847a7ae6a1462a2"],"state_sha256":"6d96e93852b115a2cc5967338350f0f26f8209dd37c96631ac5a60740eee4662"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"FUBRbbbdFqrOa4VHqfr60EOvHjZrOuRFFe+GwpSk46rpTTo0pByLxQcTuQ1L0uJRCgTZQlVLar4D8A+ycb9MDg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-03T11:18:14.846057Z","bundle_sha256":"a59a356c43cd44cb7cfb25deecb1b74e9441fd9c3ec8c883bd3d89f3a45da045"}}