{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:I7B2SWJ2AWCGEU2V74IZYIXDB2","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":"e4551f9cc93850132c5f7ef90b0bf1cb48ca74899555127ffa89a1a73e237b0a","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-03-26T10:01:01Z","title_canon_sha256":"cff71ede5db5facec7fa1cfec65fb1943e4b7814a34a22e6962e2cb388d905b5"},"schema_version":"1.0","source":{"id":"2403.17553","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2403.17553","created_at":"2026-07-05T08:00:52Z"},{"alias_kind":"arxiv_version","alias_value":"2403.17553v1","created_at":"2026-07-05T08:00:52Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2403.17553","created_at":"2026-07-05T08:00:52Z"},{"alias_kind":"pith_short_12","alias_value":"I7B2SWJ2AWCG","created_at":"2026-07-05T08:00:52Z"},{"alias_kind":"pith_short_16","alias_value":"I7B2SWJ2AWCGEU2V","created_at":"2026-07-05T08:00:52Z"},{"alias_kind":"pith_short_8","alias_value":"I7B2SWJ2","created_at":"2026-07-05T08:00:52Z"}],"graph_snapshots":[{"event_id":"sha256:ac07aceeeb1127b7fc93d2dcd67d03f32c332a0730f3f890d03c587156b48079","target":"graph","created_at":"2026-07-05T08:00:52Z","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/2403.17553/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Warning: this work contains upsetting or disturbing content.\n  Large language models (LLMs) tend to learn the social and cultural biases present in the raw pre-training data. To test if an LLM's behavior is fair, functional datasets are employed, and due to their purpose, these datasets are highly language and culture-specific. In this paper, we address a gap in the scope of multilingual bias evaluation by presenting a bias detection dataset specifically designed for the Russian language, dubbed as RuBia. The RuBia dataset is divided into 4 domains: gender, nationality, socio-economic status, ","authors_text":"Anastasiia Ivanova, Ekaterina Artemova, Ilseyar Alimova, Veronika Grigoreva","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-03-26T10:01:01Z","title":"RuBia: A Russian Language Bias Detection Dataset"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2403.17553","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":"sha256:2c4d92c9261d7b15c14800049424620f2e2b0e010e3db0864d51b7ba3f9b84d9","target":"record","created_at":"2026-07-05T08:00:52Z","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":"e4551f9cc93850132c5f7ef90b0bf1cb48ca74899555127ffa89a1a73e237b0a","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2024-03-26T10:01:01Z","title_canon_sha256":"cff71ede5db5facec7fa1cfec65fb1943e4b7814a34a22e6962e2cb388d905b5"},"schema_version":"1.0","source":{"id":"2403.17553","kind":"arxiv","version":1}},"canonical_sha256":"47c3a9593a0584625355ff119c22e30eba430ca3a088854722b763369b16adf9","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"47c3a9593a0584625355ff119c22e30eba430ca3a088854722b763369b16adf9","first_computed_at":"2026-07-05T08:00:52.304806Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T08:00:52.304806Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"+y9QKtNkgl+nNCb1QqsqS1f1isYAk8ER/iWQxPuAL3sMaoZkr9BHh4CdRPThsfF1vjnub8yCeUzx+biX26AYCg==","signature_status":"signed_v1","signed_at":"2026-07-05T08:00:52.305331Z","signed_message":"canonical_sha256_bytes"},"source_id":"2403.17553","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:2c4d92c9261d7b15c14800049424620f2e2b0e010e3db0864d51b7ba3f9b84d9","sha256:ac07aceeeb1127b7fc93d2dcd67d03f32c332a0730f3f890d03c587156b48079"],"state_sha256":"d1f19aa35cfa8beefeb7520fd0278e064514a81ddedabbf5cee03321b129ba33"}