{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:2QTU3XFH7KKY3AGYKXB662HM3S","short_pith_number":"pith:2QTU3XFH","canonical_record":{"source":{"id":"2405.20612","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2024-05-31T03:59:15Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"1f1b16ac387ec6510f095e13f41ea392205b1974f1f318f705b51bee55f2caa5","abstract_canon_sha256":"ef8e210c62696efcb959a915e1a82dd287d8070c53921e7358c7f3781c22c737"},"schema_version":"1.0"},"canonical_sha256":"d4274ddca7fa958d80d855c3ef68ecdc883c5c4f3eb8f07b784b9b2b16e9687d","source":{"kind":"arxiv","id":"2405.20612","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2405.20612","created_at":"2026-07-05T09:48:13Z"},{"alias_kind":"arxiv_version","alias_value":"2405.20612v2","created_at":"2026-07-05T09:48:13Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2405.20612","created_at":"2026-07-05T09:48:13Z"},{"alias_kind":"pith_short_12","alias_value":"2QTU3XFH7KKY","created_at":"2026-07-05T09:48:13Z"},{"alias_kind":"pith_short_16","alias_value":"2QTU3XFH7KKY3AGY","created_at":"2026-07-05T09:48:13Z"},{"alias_kind":"pith_short_8","alias_value":"2QTU3XFH","created_at":"2026-07-05T09:48:13Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:2QTU3XFH7KKY3AGYKXB662HM3S","target":"record","payload":{"canonical_record":{"source":{"id":"2405.20612","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2024-05-31T03:59:15Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"1f1b16ac387ec6510f095e13f41ea392205b1974f1f318f705b51bee55f2caa5","abstract_canon_sha256":"ef8e210c62696efcb959a915e1a82dd287d8070c53921e7358c7f3781c22c737"},"schema_version":"1.0"},"canonical_sha256":"d4274ddca7fa958d80d855c3ef68ecdc883c5c4f3eb8f07b784b9b2b16e9687d","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:48:13.829338Z","signature_b64":"vYTtNKQ/brFRsvl/oBFAdfci8CUNVb1akw9TgkPlqYheBplnvKVyoSAI7cRkkV860EIswFGM+bui0Dua6Xb6BA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"d4274ddca7fa958d80d855c3ef68ecdc883c5c4f3eb8f07b784b9b2b16e9687d","last_reissued_at":"2026-07-05T09:48:13.828898Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:48:13.828898Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2405.20612","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T09:48:13Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"0Gm4sY1qeXJ78i9SjN0MIDU0SdRyjj7kOSVcjFxmQhBJv4kwhfh2DSoGdde8I3cM7yIUyASC+J+uKxi46GcpBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-09T15:22:52.563372Z"},"content_sha256":"a2d691047ad7391bfe4a79355638ddc3001c04cde64bef9d6847075768f3be1b","schema_version":"1.0","event_id":"sha256:a2d691047ad7391bfe4a79355638ddc3001c04cde64bef9d6847075768f3be1b"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:2QTU3XFH7KKY3AGYKXB662HM3S","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"UniBias: Unveiling and Mitigating LLM Bias through Internal Attention and FFN Manipulation","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CL","authors_text":"Hanzhang Zhou, Junlang Qian, Kezhi Mao, Zijian Feng, Zixiao Zhu","submitted_at":"2024-05-31T03:59:15Z","abstract_excerpt":"Large language models (LLMs) have demonstrated impressive capabilities in various tasks using the in-context learning (ICL) paradigm. However, their effectiveness is often compromised by inherent bias, leading to prompt brittleness, i.e., sensitivity to design settings such as example selection, order, and prompt formatting. Previous studies have addressed LLM bias through external adjustment of model outputs, but the internal mechanisms that lead to such bias remain unexplored. Our work delves into these mechanisms, particularly investigating how feedforward neural networks (FFNs) and attenti"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2405.20612","kind":"arxiv","version":2},"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/2405.20612/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":"2026-07-05T09:48:13Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"FZteGDp0cuCo7Ee5H5/y8SoL83CZAyOgBEm8OXw3+Xxpgdm2KJfaYYtZTYqMgQP5qkyZpUQtXbaKCMdaHqHxAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-09T15:22:52.563887Z"},"content_sha256":"9e5a395907fd934886258e2693cbb72f2d40f6b7d8b64b8ab43b13b9b14bc08f","schema_version":"1.0","event_id":"sha256:9e5a395907fd934886258e2693cbb72f2d40f6b7d8b64b8ab43b13b9b14bc08f"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/2QTU3XFH7KKY3AGYKXB662HM3S/bundle.json","state_url":"https://pith.science/pith/2QTU3XFH7KKY3AGYKXB662HM3S/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/2QTU3XFH7KKY3AGYKXB662HM3S/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":"2026-08-09T15:22:52Z","links":{"resolver":"https://pith.science/pith/2QTU3XFH7KKY3AGYKXB662HM3S","bundle":"https://pith.science/pith/2QTU3XFH7KKY3AGYKXB662HM3S/bundle.json","state":"https://pith.science/pith/2QTU3XFH7KKY3AGYKXB662HM3S/state.json","well_known_bundle":"https://pith.science/.well-known/pith/2QTU3XFH7KKY3AGYKXB662HM3S/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:2QTU3XFH7KKY3AGYKXB662HM3S","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":"ef8e210c62696efcb959a915e1a82dd287d8070c53921e7358c7f3781c22c737","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2024-05-31T03:59:15Z","title_canon_sha256":"1f1b16ac387ec6510f095e13f41ea392205b1974f1f318f705b51bee55f2caa5"},"schema_version":"1.0","source":{"id":"2405.20612","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2405.20612","created_at":"2026-07-05T09:48:13Z"},{"alias_kind":"arxiv_version","alias_value":"2405.20612v2","created_at":"2026-07-05T09:48:13Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2405.20612","created_at":"2026-07-05T09:48:13Z"},{"alias_kind":"pith_short_12","alias_value":"2QTU3XFH7KKY","created_at":"2026-07-05T09:48:13Z"},{"alias_kind":"pith_short_16","alias_value":"2QTU3XFH7KKY3AGY","created_at":"2026-07-05T09:48:13Z"},{"alias_kind":"pith_short_8","alias_value":"2QTU3XFH","created_at":"2026-07-05T09:48:13Z"}],"graph_snapshots":[{"event_id":"sha256:9e5a395907fd934886258e2693cbb72f2d40f6b7d8b64b8ab43b13b9b14bc08f","target":"graph","created_at":"2026-07-05T09:48:13Z","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/2405.20612/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Large language models (LLMs) have demonstrated impressive capabilities in various tasks using the in-context learning (ICL) paradigm. However, their effectiveness is often compromised by inherent bias, leading to prompt brittleness, i.e., sensitivity to design settings such as example selection, order, and prompt formatting. Previous studies have addressed LLM bias through external adjustment of model outputs, but the internal mechanisms that lead to such bias remain unexplored. Our work delves into these mechanisms, particularly investigating how feedforward neural networks (FFNs) and attenti","authors_text":"Hanzhang Zhou, Junlang Qian, Kezhi Mao, Zijian Feng, Zixiao Zhu","cross_cats":["cs.AI"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2024-05-31T03:59:15Z","title":"UniBias: Unveiling and Mitigating LLM Bias through Internal Attention and FFN Manipulation"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2405.20612","kind":"arxiv","version":2},"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:a2d691047ad7391bfe4a79355638ddc3001c04cde64bef9d6847075768f3be1b","target":"record","created_at":"2026-07-05T09:48:13Z","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":"ef8e210c62696efcb959a915e1a82dd287d8070c53921e7358c7f3781c22c737","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2024-05-31T03:59:15Z","title_canon_sha256":"1f1b16ac387ec6510f095e13f41ea392205b1974f1f318f705b51bee55f2caa5"},"schema_version":"1.0","source":{"id":"2405.20612","kind":"arxiv","version":2}},"canonical_sha256":"d4274ddca7fa958d80d855c3ef68ecdc883c5c4f3eb8f07b784b9b2b16e9687d","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"d4274ddca7fa958d80d855c3ef68ecdc883c5c4f3eb8f07b784b9b2b16e9687d","first_computed_at":"2026-07-05T09:48:13.828898Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:48:13.828898Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"vYTtNKQ/brFRsvl/oBFAdfci8CUNVb1akw9TgkPlqYheBplnvKVyoSAI7cRkkV860EIswFGM+bui0Dua6Xb6BA==","signature_status":"signed_v1","signed_at":"2026-07-05T09:48:13.829338Z","signed_message":"canonical_sha256_bytes"},"source_id":"2405.20612","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:a2d691047ad7391bfe4a79355638ddc3001c04cde64bef9d6847075768f3be1b","sha256:9e5a395907fd934886258e2693cbb72f2d40f6b7d8b64b8ab43b13b9b14bc08f"],"state_sha256":"e9b601945d0a08ccc643baeb424d323f089d4e3a573c0015d2a50ae7a137f2e5"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"WW4KASj2dmXPMt7KJioCfiQe0OniceelKU/TBrLI+45vzPXiCcz5vIQ31N5nMMoeS+yRtkyJp+//fULaP/UHCg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-09T15:22:52.567958Z","bundle_sha256":"68720682ee3f2f9de39ba305fc9a46e82da4896a14d7d498f126bb98f4814742"}}