{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2025:LXBPFYKU7L46BGTNHS4WXUIUKF","short_pith_number":"pith:LXBPFYKU","schema_version":"1.0","canonical_sha256":"5dc2f2e154faf9e09a6d3cb96bd11451686faa458364af32166c9be8258cf19c","source":{"kind":"arxiv","id":"2508.06671","version":2},"attestation_state":"computed","paper":{"title":"Do Biased Models Have Biased Thoughts?","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CL","authors_text":"Abdelrahman Zayed, Reem Abdel-Salam, Shivank Garg, Swati Rajwal","submitted_at":"2025-08-08T19:41:20Z","abstract_excerpt":"The impressive performance of language models is undeniable. However, the presence of biases based on gender, race, socio-economic status, physical appearance, and sexual orientation makes the deployment of language models challenging. This paper studies the effect of chain-of-thought prompting, a recent approach that studies the steps followed by the model before it responds, on fairness. More specifically, we ask the following question: $\\textit{Do biased models have biased thoughts}$? To answer our question, we conduct experiments on $5$ popular large language models using fairness metrics "},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2508.06671","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CL","submitted_at":"2025-08-08T19:41:20Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"98ab3b1b68a577bb3b2efbb9b562ea5bb3921d73c7dc900ff5dc5220370e4dfc","abstract_canon_sha256":"18c00a97f1a0554585add118e1f9085bd34238fb53ea68c2cb5287debb0b2fe4"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:52:24.059846Z","signature_b64":"cMoQMRW2A4CfUX7kjfpq1FjeZt0ibaAOvwc67fjhPvA8LUVIdPLmGjnfSTXCjO+HjDWqQ4dLsDpBtCpy6T3EAA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"5dc2f2e154faf9e09a6d3cb96bd11451686faa458364af32166c9be8258cf19c","last_reissued_at":"2026-07-05T11:52:24.059430Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:52:24.059430Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Do Biased Models Have Biased Thoughts?","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CL","authors_text":"Abdelrahman Zayed, Reem Abdel-Salam, Shivank Garg, Swati Rajwal","submitted_at":"2025-08-08T19:41:20Z","abstract_excerpt":"The impressive performance of language models is undeniable. However, the presence of biases based on gender, race, socio-economic status, physical appearance, and sexual orientation makes the deployment of language models challenging. This paper studies the effect of chain-of-thought prompting, a recent approach that studies the steps followed by the model before it responds, on fairness. More specifically, we ask the following question: $\\textit{Do biased models have biased thoughts}$? To answer our question, we conduct experiments on $5$ popular large language models using fairness metrics "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2508.06671","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/2508.06671/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"},"aliases":[{"alias_kind":"arxiv","alias_value":"2508.06671","created_at":"2026-07-05T11:52:24.059486+00:00"},{"alias_kind":"arxiv_version","alias_value":"2508.06671v2","created_at":"2026-07-05T11:52:24.059486+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2508.06671","created_at":"2026-07-05T11:52:24.059486+00:00"},{"alias_kind":"pith_short_12","alias_value":"LXBPFYKU7L46","created_at":"2026-07-05T11:52:24.059486+00:00"},{"alias_kind":"pith_short_16","alias_value":"LXBPFYKU7L46BGTN","created_at":"2026-07-05T11:52:24.059486+00:00"},{"alias_kind":"pith_short_8","alias_value":"LXBPFYKU","created_at":"2026-07-05T11:52:24.059486+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/LXBPFYKU7L46BGTNHS4WXUIUKF","json":"https://pith.science/pith/LXBPFYKU7L46BGTNHS4WXUIUKF.json","graph_json":"https://pith.science/api/pith-number/LXBPFYKU7L46BGTNHS4WXUIUKF/graph.json","events_json":"https://pith.science/api/pith-number/LXBPFYKU7L46BGTNHS4WXUIUKF/events.json","paper":"https://pith.science/paper/LXBPFYKU"},"agent_actions":{"view_html":"https://pith.science/pith/LXBPFYKU7L46BGTNHS4WXUIUKF","download_json":"https://pith.science/pith/LXBPFYKU7L46BGTNHS4WXUIUKF.json","view_paper":"https://pith.science/paper/LXBPFYKU","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2508.06671&json=true","fetch_graph":"https://pith.science/api/pith-number/LXBPFYKU7L46BGTNHS4WXUIUKF/graph.json","fetch_events":"https://pith.science/api/pith-number/LXBPFYKU7L46BGTNHS4WXUIUKF/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/LXBPFYKU7L46BGTNHS4WXUIUKF/action/timestamp_anchor","attest_storage":"https://pith.science/pith/LXBPFYKU7L46BGTNHS4WXUIUKF/action/storage_attestation","attest_author":"https://pith.science/pith/LXBPFYKU7L46BGTNHS4WXUIUKF/action/author_attestation","sign_citation":"https://pith.science/pith/LXBPFYKU7L46BGTNHS4WXUIUKF/action/citation_signature","submit_replication":"https://pith.science/pith/LXBPFYKU7L46BGTNHS4WXUIUKF/action/replication_record"}},"created_at":"2026-07-05T11:52:24.059486+00:00","updated_at":"2026-07-05T11:52:24.059486+00:00"}