{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:WPA7EOSPMMBXGCO5VQFRXMR6T7","short_pith_number":"pith:WPA7EOSP","canonical_record":{"source":{"id":"2410.12864","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.CL","submitted_at":"2024-10-13T03:43:18Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"235ff816050d90ff8a20b3e609d83aca55b00956649077a7554e1aa930848378","abstract_canon_sha256":"037ceb9e2fa3a2f7820139412fc1df8246694dca442790257e2adc925f523d0e"},"schema_version":"1.0"},"canonical_sha256":"b3c1f23a4f63037309ddac0b1bb23e9fe124a508b15dc764d19ddb08e9eec404","source":{"kind":"arxiv","id":"2410.12864","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2410.12864","created_at":"2026-07-05T09:21:52Z"},{"alias_kind":"arxiv_version","alias_value":"2410.12864v1","created_at":"2026-07-05T09:21:52Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2410.12864","created_at":"2026-07-05T09:21:52Z"},{"alias_kind":"pith_short_12","alias_value":"WPA7EOSPMMBX","created_at":"2026-07-05T09:21:52Z"},{"alias_kind":"pith_short_16","alias_value":"WPA7EOSPMMBXGCO5","created_at":"2026-07-05T09:21:52Z"},{"alias_kind":"pith_short_8","alias_value":"WPA7EOSP","created_at":"2026-07-05T09:21:52Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:WPA7EOSPMMBXGCO5VQFRXMR6T7","target":"record","payload":{"canonical_record":{"source":{"id":"2410.12864","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.CL","submitted_at":"2024-10-13T03:43:18Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"235ff816050d90ff8a20b3e609d83aca55b00956649077a7554e1aa930848378","abstract_canon_sha256":"037ceb9e2fa3a2f7820139412fc1df8246694dca442790257e2adc925f523d0e"},"schema_version":"1.0"},"canonical_sha256":"b3c1f23a4f63037309ddac0b1bb23e9fe124a508b15dc764d19ddb08e9eec404","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:21:52.168959Z","signature_b64":"ikeavf9Wqgn4c+rJz1coItqexsyPRLTdDOV3BccPrmRcrFID6hiDpo6zo/7TLwVdwWn5FMXhpNXSDQxCTr7tCA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"b3c1f23a4f63037309ddac0b1bb23e9fe124a508b15dc764d19ddb08e9eec404","last_reissued_at":"2026-07-05T09:21:52.168527Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:21:52.168527Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2410.12864","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":"2026-07-05T09:21:52Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"cH0KG0GHkl60lZ/1eKNhhWZH+mcyKVgLp8vfPJyhm1Yb7roTpfBBNzLD1kv24mlAZ4xWWrAdJ6D5D0h9LwjaBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-07T09:04:49.829092Z"},"content_sha256":"85b27d4e32606e984729a588f74c724fc368291f322980c88682506fb81f122d","schema_version":"1.0","event_id":"sha256:85b27d4e32606e984729a588f74c724fc368291f322980c88682506fb81f122d"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:WPA7EOSPMMBXGCO5VQFRXMR6T7","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Investigating Implicit Bias in Large Language Models: A Large-Scale Study of Over 50 LLMs","license":"http://creativecommons.org/licenses/by-sa/4.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CL","authors_text":"Divyanshu Kumar, Prashanth Harshangi, Sahil Agarwal, Umang Jain","submitted_at":"2024-10-13T03:43:18Z","abstract_excerpt":"Large Language Models (LLMs) are being adopted across a wide range of tasks, including decision-making processes in industries where bias in AI systems is a significant concern. Recent research indicates that LLMs can harbor implicit biases even when they pass explicit bias evaluations. Building upon the frameworks of the LLM Implicit Association Test (IAT) Bias and LLM Decision Bias, this study highlights that newer or larger language models do not automatically exhibit reduced bias; in some cases, they displayed higher bias scores than their predecessors, such as in Meta's Llama series and O"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2410.12864","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/2410.12864/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":"2026-07-05T09:21:52Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"a8egeJW3o1mztZDCabkELMsJv0E1IuOzDqUvl4x2/1uM62CV/Hm58o1dHyeEUVFi40XfhoxcgFnBUY3gjkiXBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-07T09:04:49.829482Z"},"content_sha256":"8534236180257f168287e21d04970cbc0b44b1bdaa30c32803838d60284ca226","schema_version":"1.0","event_id":"sha256:8534236180257f168287e21d04970cbc0b44b1bdaa30c32803838d60284ca226"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/WPA7EOSPMMBXGCO5VQFRXMR6T7/bundle.json","state_url":"https://pith.science/pith/WPA7EOSPMMBXGCO5VQFRXMR6T7/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/WPA7EOSPMMBXGCO5VQFRXMR6T7/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":"2026-07-07T09:04:49Z","links":{"resolver":"https://pith.science/pith/WPA7EOSPMMBXGCO5VQFRXMR6T7","bundle":"https://pith.science/pith/WPA7EOSPMMBXGCO5VQFRXMR6T7/bundle.json","state":"https://pith.science/pith/WPA7EOSPMMBXGCO5VQFRXMR6T7/state.json","well_known_bundle":"https://pith.science/.well-known/pith/WPA7EOSPMMBXGCO5VQFRXMR6T7/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:WPA7EOSPMMBXGCO5VQFRXMR6T7","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":"037ceb9e2fa3a2f7820139412fc1df8246694dca442790257e2adc925f523d0e","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.CL","submitted_at":"2024-10-13T03:43:18Z","title_canon_sha256":"235ff816050d90ff8a20b3e609d83aca55b00956649077a7554e1aa930848378"},"schema_version":"1.0","source":{"id":"2410.12864","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2410.12864","created_at":"2026-07-05T09:21:52Z"},{"alias_kind":"arxiv_version","alias_value":"2410.12864v1","created_at":"2026-07-05T09:21:52Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2410.12864","created_at":"2026-07-05T09:21:52Z"},{"alias_kind":"pith_short_12","alias_value":"WPA7EOSPMMBX","created_at":"2026-07-05T09:21:52Z"},{"alias_kind":"pith_short_16","alias_value":"WPA7EOSPMMBXGCO5","created_at":"2026-07-05T09:21:52Z"},{"alias_kind":"pith_short_8","alias_value":"WPA7EOSP","created_at":"2026-07-05T09:21:52Z"}],"graph_snapshots":[{"event_id":"sha256:8534236180257f168287e21d04970cbc0b44b1bdaa30c32803838d60284ca226","target":"graph","created_at":"2026-07-05T09:21:52Z","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/2410.12864/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Large Language Models (LLMs) are being adopted across a wide range of tasks, including decision-making processes in industries where bias in AI systems is a significant concern. Recent research indicates that LLMs can harbor implicit biases even when they pass explicit bias evaluations. Building upon the frameworks of the LLM Implicit Association Test (IAT) Bias and LLM Decision Bias, this study highlights that newer or larger language models do not automatically exhibit reduced bias; in some cases, they displayed higher bias scores than their predecessors, such as in Meta's Llama series and O","authors_text":"Divyanshu Kumar, Prashanth Harshangi, Sahil Agarwal, Umang Jain","cross_cats":["cs.AI"],"headline":"","license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.CL","submitted_at":"2024-10-13T03:43:18Z","title":"Investigating Implicit Bias in Large Language Models: A Large-Scale Study of Over 50 LLMs"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2410.12864","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":"sha256:85b27d4e32606e984729a588f74c724fc368291f322980c88682506fb81f122d","target":"record","created_at":"2026-07-05T09:21:52Z","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":"037ceb9e2fa3a2f7820139412fc1df8246694dca442790257e2adc925f523d0e","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by-sa/4.0/","primary_cat":"cs.CL","submitted_at":"2024-10-13T03:43:18Z","title_canon_sha256":"235ff816050d90ff8a20b3e609d83aca55b00956649077a7554e1aa930848378"},"schema_version":"1.0","source":{"id":"2410.12864","kind":"arxiv","version":1}},"canonical_sha256":"b3c1f23a4f63037309ddac0b1bb23e9fe124a508b15dc764d19ddb08e9eec404","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"b3c1f23a4f63037309ddac0b1bb23e9fe124a508b15dc764d19ddb08e9eec404","first_computed_at":"2026-07-05T09:21:52.168527Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:21:52.168527Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"ikeavf9Wqgn4c+rJz1coItqexsyPRLTdDOV3BccPrmRcrFID6hiDpo6zo/7TLwVdwWn5FMXhpNXSDQxCTr7tCA==","signature_status":"signed_v1","signed_at":"2026-07-05T09:21:52.168959Z","signed_message":"canonical_sha256_bytes"},"source_id":"2410.12864","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:85b27d4e32606e984729a588f74c724fc368291f322980c88682506fb81f122d","sha256:8534236180257f168287e21d04970cbc0b44b1bdaa30c32803838d60284ca226"],"state_sha256":"4c3a0999e7a90f3d10884977f7ae8716018e38f4413faa95ea15e8743e528fa9"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"eOewkcTJKxhF5jjSbPg9kDmmpOE/ChvTZ+cFrCd+W09u9vXu44ynpOmarrgj7xdriCgW93xv78DcXXS6250ODA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-07T09:04:49.831844Z","bundle_sha256":"e5e57f4d8c55e3d69fb08acc654fc511e28fa752665a61624a5e0222171da06c"}}