{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:CRYJCCG7B5LMCEYFUWYXBJ3CXW","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":"ce3b42b57eee4cab47e20736e79973a02191a25829bea313d425c338f57a6bab","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2025-03-08T04:43:01Z","title_canon_sha256":"68fea142905e8051a6311079e924b0b36fa414994a56bf7f14a4896929b5af22"},"schema_version":"1.0","source":{"id":"2503.06054","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2503.06054","created_at":"2026-07-05T10:26:52Z"},{"alias_kind":"arxiv_version","alias_value":"2503.06054v1","created_at":"2026-07-05T10:26:52Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2503.06054","created_at":"2026-07-05T10:26:52Z"},{"alias_kind":"pith_short_12","alias_value":"CRYJCCG7B5LM","created_at":"2026-07-05T10:26:52Z"},{"alias_kind":"pith_short_16","alias_value":"CRYJCCG7B5LMCEYF","created_at":"2026-07-05T10:26:52Z"},{"alias_kind":"pith_short_8","alias_value":"CRYJCCG7","created_at":"2026-07-05T10:26:52Z"}],"graph_snapshots":[{"event_id":"sha256:457b86d87fff331062b28feba3b0c04979629729cfc52f924bc6a93106da2634","target":"graph","created_at":"2026-07-05T10:26:52Z","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/2503.06054/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Recent advancements in Artificial Intelligence, particularly in Large Language Models (LLMs), have transformed natural language processing by improving generative capabilities. However, detecting biases embedded within these models remains a challenge. Subtle biases can propagate misinformation, influence decision-making, and reinforce stereotypes, raising ethical concerns. This study presents a detection framework to identify nuanced biases in LLMs. The approach integrates contextual analysis, interpretability via attention mechanisms, and counterfactual data augmentation to capture hidden bi","authors_text":"Suvendu Mohanty","cross_cats":["cs.AI"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2025-03-08T04:43:01Z","title":"Fine-Grained Bias Detection in LLM: Enhancing detection mechanisms for nuanced biases"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2503.06054","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:f9a45b873d5285abb2ccb8fcca3968dfcfc91b585918d3a495a28ed1313634e3","target":"record","created_at":"2026-07-05T10:26:52Z","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":"ce3b42b57eee4cab47e20736e79973a02191a25829bea313d425c338f57a6bab","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2025-03-08T04:43:01Z","title_canon_sha256":"68fea142905e8051a6311079e924b0b36fa414994a56bf7f14a4896929b5af22"},"schema_version":"1.0","source":{"id":"2503.06054","kind":"arxiv","version":1}},"canonical_sha256":"14709108df0f56c11305a5b170a762bda098cb906369cc50d9092b95812c161f","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"14709108df0f56c11305a5b170a762bda098cb906369cc50d9092b95812c161f","first_computed_at":"2026-07-05T10:26:52.818697Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:26:52.818697Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"9XYBoxn4ynt50ue8jP4aXSMiRAEiNihMHC0+86i5lKB9F33C9TUOCcEL0PrLQoTApYSDnjnE3FGhXSls3b9ZCQ==","signature_status":"signed_v1","signed_at":"2026-07-05T10:26:52.819168Z","signed_message":"canonical_sha256_bytes"},"source_id":"2503.06054","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:f9a45b873d5285abb2ccb8fcca3968dfcfc91b585918d3a495a28ed1313634e3","sha256:457b86d87fff331062b28feba3b0c04979629729cfc52f924bc6a93106da2634"],"state_sha256":"47e2a7a081b59a37fc4e298e29336b2dcce804a50a99bd380ffb82574b13d221"}