{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:FUCGSM4T46PCSNZHHB57DZXOZM","short_pith_number":"pith:FUCGSM4T","canonical_record":{"source":{"id":"2305.18569","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-05-22T17:51:56Z","cross_cats_sorted":["cs.AI","cs.CL","cs.CY"],"title_canon_sha256":"9378689e055e99b9e464f39d08c827d4544e2dc00a1c025f055ef4eae8839d60","abstract_canon_sha256":"07a0226b5b480e0d3349e5a08d1058a95a9697b290920c24264e06b6a505963d"},"schema_version":"1.0"},"canonical_sha256":"2d04693393e79e293727387bf1e6eecb2123f995deba5eca1e047939a14381cc","source":{"kind":"arxiv","id":"2305.18569","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2305.18569","created_at":"2026-07-05T08:15:37Z"},{"alias_kind":"arxiv_version","alias_value":"2305.18569v2","created_at":"2026-07-05T08:15:37Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2305.18569","created_at":"2026-07-05T08:15:37Z"},{"alias_kind":"pith_short_12","alias_value":"FUCGSM4T46PC","created_at":"2026-07-05T08:15:37Z"},{"alias_kind":"pith_short_16","alias_value":"FUCGSM4T46PCSNZH","created_at":"2026-07-05T08:15:37Z"},{"alias_kind":"pith_short_8","alias_value":"FUCGSM4T","created_at":"2026-07-05T08:15:37Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:FUCGSM4T46PCSNZHHB57DZXOZM","target":"record","payload":{"canonical_record":{"source":{"id":"2305.18569","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-05-22T17:51:56Z","cross_cats_sorted":["cs.AI","cs.CL","cs.CY"],"title_canon_sha256":"9378689e055e99b9e464f39d08c827d4544e2dc00a1c025f055ef4eae8839d60","abstract_canon_sha256":"07a0226b5b480e0d3349e5a08d1058a95a9697b290920c24264e06b6a505963d"},"schema_version":"1.0"},"canonical_sha256":"2d04693393e79e293727387bf1e6eecb2123f995deba5eca1e047939a14381cc","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T08:15:37.033673Z","signature_b64":"Lu18HPsU2CO3WA6M8zcD06B2W/C9ae9ymD7OjP33obcQAUTNU1kcJ2TYpvDPAuyyBYwI6v9FJnjypjtfJYrsCA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"2d04693393e79e293727387bf1e6eecb2123f995deba5eca1e047939a14381cc","last_reissued_at":"2026-07-05T08:15:37.033158Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T08:15:37.033158Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2305.18569","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":"2026-07-05T08:15:37Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"hXRquN5Z3YRY7w0pBljoE5njQ2CKmtFvy5+De7SQC58OuLu9tCjfPTzMoydewVyW8LlqlWxlCFbHs2lCM1f7DA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-10T11:46:25.821323Z"},"content_sha256":"8bc7e115e1ad02de8746b4138fb50b4e30fd18134881a6ea7275727ae29dd672","schema_version":"1.0","event_id":"sha256:8bc7e115e1ad02de8746b4138fb50b4e30fd18134881a6ea7275727ae29dd672"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:FUCGSM4T46PCSNZHHB57DZXOZM","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Fairness of ChatGPT","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI","cs.CL","cs.CY"],"primary_cat":"cs.LG","authors_text":"Lanjing Zhang, Yongfeng Zhang, Yunqi Li","submitted_at":"2023-05-22T17:51:56Z","abstract_excerpt":"Understanding and addressing unfairness in LLMs are crucial for responsible AI deployment. However, there is a limited number of quantitative analyses and in-depth studies regarding fairness evaluations in LLMs, especially when applying LLMs to high-stakes fields. This work aims to fill this gap by providing a systematic evaluation of the effectiveness and fairness of LLMs using ChatGPT as a study case. We focus on assessing ChatGPT's performance in high-takes fields including education, criminology, finance and healthcare. To conduct a thorough evaluation, we consider both group fairness and "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2305.18569","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/2305.18569/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":"2026-07-05T08:15:37Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"kH85xr/6+Rk7q06hPLkKQvOclZchZReeCyQfKpV59Ac9N6MYzXvbJvjRY8N8xSQ9CiK+s9+Qj84yhiDJjVIkDg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-10T11:46:25.822220Z"},"content_sha256":"9043d80d572521219aa5c947611713f8ef5bc5e3e64cef16141f85a9ddc0fc50","schema_version":"1.0","event_id":"sha256:9043d80d572521219aa5c947611713f8ef5bc5e3e64cef16141f85a9ddc0fc50"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/FUCGSM4T46PCSNZHHB57DZXOZM/bundle.json","state_url":"https://pith.science/pith/FUCGSM4T46PCSNZHHB57DZXOZM/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/FUCGSM4T46PCSNZHHB57DZXOZM/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":"2026-08-10T11:46:25Z","links":{"resolver":"https://pith.science/pith/FUCGSM4T46PCSNZHHB57DZXOZM","bundle":"https://pith.science/pith/FUCGSM4T46PCSNZHHB57DZXOZM/bundle.json","state":"https://pith.science/pith/FUCGSM4T46PCSNZHHB57DZXOZM/state.json","well_known_bundle":"https://pith.science/.well-known/pith/FUCGSM4T46PCSNZHHB57DZXOZM/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:FUCGSM4T46PCSNZHHB57DZXOZM","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":"07a0226b5b480e0d3349e5a08d1058a95a9697b290920c24264e06b6a505963d","cross_cats_sorted":["cs.AI","cs.CL","cs.CY"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-05-22T17:51:56Z","title_canon_sha256":"9378689e055e99b9e464f39d08c827d4544e2dc00a1c025f055ef4eae8839d60"},"schema_version":"1.0","source":{"id":"2305.18569","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2305.18569","created_at":"2026-07-05T08:15:37Z"},{"alias_kind":"arxiv_version","alias_value":"2305.18569v2","created_at":"2026-07-05T08:15:37Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2305.18569","created_at":"2026-07-05T08:15:37Z"},{"alias_kind":"pith_short_12","alias_value":"FUCGSM4T46PC","created_at":"2026-07-05T08:15:37Z"},{"alias_kind":"pith_short_16","alias_value":"FUCGSM4T46PCSNZH","created_at":"2026-07-05T08:15:37Z"},{"alias_kind":"pith_short_8","alias_value":"FUCGSM4T","created_at":"2026-07-05T08:15:37Z"}],"graph_snapshots":[{"event_id":"sha256:9043d80d572521219aa5c947611713f8ef5bc5e3e64cef16141f85a9ddc0fc50","target":"graph","created_at":"2026-07-05T08:15:37Z","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/2305.18569/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Understanding and addressing unfairness in LLMs are crucial for responsible AI deployment. However, there is a limited number of quantitative analyses and in-depth studies regarding fairness evaluations in LLMs, especially when applying LLMs to high-stakes fields. This work aims to fill this gap by providing a systematic evaluation of the effectiveness and fairness of LLMs using ChatGPT as a study case. We focus on assessing ChatGPT's performance in high-takes fields including education, criminology, finance and healthcare. To conduct a thorough evaluation, we consider both group fairness and ","authors_text":"Lanjing Zhang, Yongfeng Zhang, Yunqi Li","cross_cats":["cs.AI","cs.CL","cs.CY"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-05-22T17:51:56Z","title":"Fairness of ChatGPT"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2305.18569","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":"sha256:8bc7e115e1ad02de8746b4138fb50b4e30fd18134881a6ea7275727ae29dd672","target":"record","created_at":"2026-07-05T08:15:37Z","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":"07a0226b5b480e0d3349e5a08d1058a95a9697b290920c24264e06b6a505963d","cross_cats_sorted":["cs.AI","cs.CL","cs.CY"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-05-22T17:51:56Z","title_canon_sha256":"9378689e055e99b9e464f39d08c827d4544e2dc00a1c025f055ef4eae8839d60"},"schema_version":"1.0","source":{"id":"2305.18569","kind":"arxiv","version":2}},"canonical_sha256":"2d04693393e79e293727387bf1e6eecb2123f995deba5eca1e047939a14381cc","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"2d04693393e79e293727387bf1e6eecb2123f995deba5eca1e047939a14381cc","first_computed_at":"2026-07-05T08:15:37.033158Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T08:15:37.033158Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Lu18HPsU2CO3WA6M8zcD06B2W/C9ae9ymD7OjP33obcQAUTNU1kcJ2TYpvDPAuyyBYwI6v9FJnjypjtfJYrsCA==","signature_status":"signed_v1","signed_at":"2026-07-05T08:15:37.033673Z","signed_message":"canonical_sha256_bytes"},"source_id":"2305.18569","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:8bc7e115e1ad02de8746b4138fb50b4e30fd18134881a6ea7275727ae29dd672","sha256:9043d80d572521219aa5c947611713f8ef5bc5e3e64cef16141f85a9ddc0fc50"],"state_sha256":"fe84d6fd9a914c81b5393b66ba208d576f0bcb3692ba2064f84fb0ca92c6eb65"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"PcjjQgrQL3Ae8600SOJsMDiRYV7fnToqdkNVUCQCAdf3p2yWTX82SUou/Ku/JyywGmozZB6RSasKMx2mC3vyCg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-10T11:46:25.829363Z","bundle_sha256":"802191fca85e6b40dab5762c8d14be40cbf4eee3503e6059c3114f233b996241"}}