{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:MGW3OIR7OBM7Y7BZJAWKH4LMEW","short_pith_number":"pith:MGW3OIR7","canonical_record":{"source":{"id":"2308.10149","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2023-08-20T03:30:22Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"a760557488b5641b3441b9daf3c87dcd05ecf800cdd943c052317479b47a8b9e","abstract_canon_sha256":"922f6103765349f43e46966b8969d2216e7dac5deaf513e0269849a1cc4615f3"},"schema_version":"1.0"},"canonical_sha256":"61adb7223f7059fc7c39482ca3f16c25898f463e756cf30c06f7a790ad26a764","source":{"kind":"arxiv","id":"2308.10149","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2308.10149","created_at":"2026-07-05T07:47:44Z"},{"alias_kind":"arxiv_version","alias_value":"2308.10149v2","created_at":"2026-07-05T07:47:44Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2308.10149","created_at":"2026-07-05T07:47:44Z"},{"alias_kind":"pith_short_12","alias_value":"MGW3OIR7OBM7","created_at":"2026-07-05T07:47:44Z"},{"alias_kind":"pith_short_16","alias_value":"MGW3OIR7OBM7Y7BZ","created_at":"2026-07-05T07:47:44Z"},{"alias_kind":"pith_short_8","alias_value":"MGW3OIR7","created_at":"2026-07-05T07:47:44Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:MGW3OIR7OBM7Y7BZJAWKH4LMEW","target":"record","payload":{"canonical_record":{"source":{"id":"2308.10149","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2023-08-20T03:30:22Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"a760557488b5641b3441b9daf3c87dcd05ecf800cdd943c052317479b47a8b9e","abstract_canon_sha256":"922f6103765349f43e46966b8969d2216e7dac5deaf513e0269849a1cc4615f3"},"schema_version":"1.0"},"canonical_sha256":"61adb7223f7059fc7c39482ca3f16c25898f463e756cf30c06f7a790ad26a764","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T07:47:44.512864Z","signature_b64":"LHIL5BArQsq92192Jif/XebERW1jx85iJRT5tCxW/xM3S9A3NvYgwQ5Ojr20jLCadaDhi107yi6AceU5eWVqDg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"61adb7223f7059fc7c39482ca3f16c25898f463e756cf30c06f7a790ad26a764","last_reissued_at":"2026-07-05T07:47:44.512362Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T07:47:44.512362Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2308.10149","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":"2026-07-05T07:47:44Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"CtRTovAmkggEHn/C9YmfmvR2POOImheO7mCjW6SQdoMF1eLih4Ei7am+qDXR8/Pr8z2n8UX9KLVdKGuRz/PqDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-06T20:28:33.116046Z"},"content_sha256":"88b3066c080005db593f10ea47dcffc85a66272439bfdd7146b6df52e656632f","schema_version":"1.0","event_id":"sha256:88b3066c080005db593f10ea47dcffc85a66272439bfdd7146b6df52e656632f"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:MGW3OIR7OBM7Y7BZJAWKH4LMEW","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"A Survey on Fairness in Large Language Models","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CL","authors_text":"Mengnan Du, Rui Song, Xin Wang, Yingji Li, Ying Wang","submitted_at":"2023-08-20T03:30:22Z","abstract_excerpt":"Large Language Models (LLMs) have shown powerful performance and development prospects and are widely deployed in the real world. However, LLMs can capture social biases from unprocessed training data and propagate the biases to downstream tasks. Unfair LLM systems have undesirable social impacts and potential harms. In this paper, we provide a comprehensive review of related research on fairness in LLMs. Considering the influence of parameter magnitude and training paradigm on research strategy, we divide existing fairness research into oriented to medium-sized LLMs under pre-training and fin"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2308.10149","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/2308.10149/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":"2026-07-05T07:47:44Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"wHsnrgEOa+2Ws9VFcUZsyJCrr7oOPtgWs3SxPt3x4vGFD1fkMBGs95VT/OtJBbKjxz+loEbBU5SRqaxgrlOnCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-06T20:28:33.116620Z"},"content_sha256":"18fc611aec96bbff473be050d73202f99e8e495108c7696fa04afd19fce14257","schema_version":"1.0","event_id":"sha256:18fc611aec96bbff473be050d73202f99e8e495108c7696fa04afd19fce14257"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/MGW3OIR7OBM7Y7BZJAWKH4LMEW/bundle.json","state_url":"https://pith.science/pith/MGW3OIR7OBM7Y7BZJAWKH4LMEW/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/MGW3OIR7OBM7Y7BZJAWKH4LMEW/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":"2026-08-06T20:28:33Z","links":{"resolver":"https://pith.science/pith/MGW3OIR7OBM7Y7BZJAWKH4LMEW","bundle":"https://pith.science/pith/MGW3OIR7OBM7Y7BZJAWKH4LMEW/bundle.json","state":"https://pith.science/pith/MGW3OIR7OBM7Y7BZJAWKH4LMEW/state.json","well_known_bundle":"https://pith.science/.well-known/pith/MGW3OIR7OBM7Y7BZJAWKH4LMEW/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:MGW3OIR7OBM7Y7BZJAWKH4LMEW","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":"922f6103765349f43e46966b8969d2216e7dac5deaf513e0269849a1cc4615f3","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2023-08-20T03:30:22Z","title_canon_sha256":"a760557488b5641b3441b9daf3c87dcd05ecf800cdd943c052317479b47a8b9e"},"schema_version":"1.0","source":{"id":"2308.10149","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2308.10149","created_at":"2026-07-05T07:47:44Z"},{"alias_kind":"arxiv_version","alias_value":"2308.10149v2","created_at":"2026-07-05T07:47:44Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2308.10149","created_at":"2026-07-05T07:47:44Z"},{"alias_kind":"pith_short_12","alias_value":"MGW3OIR7OBM7","created_at":"2026-07-05T07:47:44Z"},{"alias_kind":"pith_short_16","alias_value":"MGW3OIR7OBM7Y7BZ","created_at":"2026-07-05T07:47:44Z"},{"alias_kind":"pith_short_8","alias_value":"MGW3OIR7","created_at":"2026-07-05T07:47:44Z"}],"graph_snapshots":[{"event_id":"sha256:18fc611aec96bbff473be050d73202f99e8e495108c7696fa04afd19fce14257","target":"graph","created_at":"2026-07-05T07:47:44Z","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/2308.10149/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Large Language Models (LLMs) have shown powerful performance and development prospects and are widely deployed in the real world. However, LLMs can capture social biases from unprocessed training data and propagate the biases to downstream tasks. Unfair LLM systems have undesirable social impacts and potential harms. In this paper, we provide a comprehensive review of related research on fairness in LLMs. Considering the influence of parameter magnitude and training paradigm on research strategy, we divide existing fairness research into oriented to medium-sized LLMs under pre-training and fin","authors_text":"Mengnan Du, Rui Song, Xin Wang, Yingji Li, Ying Wang","cross_cats":["cs.AI"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2023-08-20T03:30:22Z","title":"A Survey on Fairness in Large Language Models"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2308.10149","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":"sha256:88b3066c080005db593f10ea47dcffc85a66272439bfdd7146b6df52e656632f","target":"record","created_at":"2026-07-05T07:47:44Z","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":"922f6103765349f43e46966b8969d2216e7dac5deaf513e0269849a1cc4615f3","cross_cats_sorted":["cs.AI"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CL","submitted_at":"2023-08-20T03:30:22Z","title_canon_sha256":"a760557488b5641b3441b9daf3c87dcd05ecf800cdd943c052317479b47a8b9e"},"schema_version":"1.0","source":{"id":"2308.10149","kind":"arxiv","version":2}},"canonical_sha256":"61adb7223f7059fc7c39482ca3f16c25898f463e756cf30c06f7a790ad26a764","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"61adb7223f7059fc7c39482ca3f16c25898f463e756cf30c06f7a790ad26a764","first_computed_at":"2026-07-05T07:47:44.512362Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T07:47:44.512362Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"LHIL5BArQsq92192Jif/XebERW1jx85iJRT5tCxW/xM3S9A3NvYgwQ5Ojr20jLCadaDhi107yi6AceU5eWVqDg==","signature_status":"signed_v1","signed_at":"2026-07-05T07:47:44.512864Z","signed_message":"canonical_sha256_bytes"},"source_id":"2308.10149","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:88b3066c080005db593f10ea47dcffc85a66272439bfdd7146b6df52e656632f","sha256:18fc611aec96bbff473be050d73202f99e8e495108c7696fa04afd19fce14257"],"state_sha256":"9934ced5440a140165f85db642c61d284cc5f44ca8e715e751347019c280b1ff"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"l0Uf99bMVPctuJj/SsQY9OiSBmcSCEumWkUyP5R9FxpvkGV9jcLv6hdH5If5wd3AW6KGub6F7b7xKj/n47zHDA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-06T20:28:33.120759Z","bundle_sha256":"a65fab87853d59de1233ab828f42c746885bdf99840a9cf678019ae260252a11"}}