{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:LSDY74P3UFLKXJVWMO4SGEM5KT","short_pith_number":"pith:LSDY74P3","canonical_record":{"source":{"id":"2506.05390","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CL","submitted_at":"2025-06-03T18:14:57Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"c5549c592184c4b69bb382db1bcf37684fb077b13f4d909196f2cb42d9e9542e","abstract_canon_sha256":"bcc6dee75e309d8fa366b5296726573eabdb8b237a53cf7c9efa889a9a131fdc"},"schema_version":"1.0"},"canonical_sha256":"5c878ff1fba156aba6b663b923119d54f1fbac137578fdcefe367dca8589c94c","source":{"kind":"arxiv","id":"2506.05390","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2506.05390","created_at":"2026-07-05T11:17:01Z"},{"alias_kind":"arxiv_version","alias_value":"2506.05390v1","created_at":"2026-07-05T11:17:01Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2506.05390","created_at":"2026-07-05T11:17:01Z"},{"alias_kind":"pith_short_12","alias_value":"LSDY74P3UFLK","created_at":"2026-07-05T11:17:01Z"},{"alias_kind":"pith_short_16","alias_value":"LSDY74P3UFLKXJVW","created_at":"2026-07-05T11:17:01Z"},{"alias_kind":"pith_short_8","alias_value":"LSDY74P3","created_at":"2026-07-05T11:17:01Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:LSDY74P3UFLKXJVWMO4SGEM5KT","target":"record","payload":{"canonical_record":{"source":{"id":"2506.05390","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CL","submitted_at":"2025-06-03T18:14:57Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"c5549c592184c4b69bb382db1bcf37684fb077b13f4d909196f2cb42d9e9542e","abstract_canon_sha256":"bcc6dee75e309d8fa366b5296726573eabdb8b237a53cf7c9efa889a9a131fdc"},"schema_version":"1.0"},"canonical_sha256":"5c878ff1fba156aba6b663b923119d54f1fbac137578fdcefe367dca8589c94c","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:17:01.868626Z","signature_b64":"nFBmg0VGRp2CjxFvOrAK0NjlzqAw4XvJU9fWKlqJbTcF06QzjACnGwhUP9VBqjNxFaQxiHvquG9P1gjgiK2cAQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"5c878ff1fba156aba6b663b923119d54f1fbac137578fdcefe367dca8589c94c","last_reissued_at":"2026-07-05T11:17:01.868165Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:17:01.868165Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2506.05390","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":"2026-07-05T11:17:01Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"qFXeTz2ucFWjFuBJPXRQSLe0QCUDp6EfBIXq+eadYyJ4StE5JWq+CGixjIf1hX02IVZa1P8K7jDbvLbo8gGwDg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-10T01:44:07.518809Z"},"content_sha256":"539e6d2182a8f4dc3aeb78b85b39aef191497688b2033be7fe635f495153660c","schema_version":"1.0","event_id":"sha256:539e6d2182a8f4dc3aeb78b85b39aef191497688b2033be7fe635f495153660c"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:LSDY74P3UFLKXJVWMO4SGEM5KT","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Understanding Gender Bias in AI-Generated Product Descriptions","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"cs.CL","authors_text":"Lauren Wilcox, Markelle Kelly, Mohammad Tahaei, Padhraic Smyth","submitted_at":"2025-06-03T18:14:57Z","abstract_excerpt":"While gender bias in large language models (LLMs) has been extensively studied in many domains, uses of LLMs in e-commerce remain largely unexamined and may reveal novel forms of algorithmic bias and harm. Our work investigates this space, developing data-driven taxonomic categories of gender bias in the context of product description generation, which we situate with respect to existing general purpose harms taxonomies. We illustrate how AI-generated product descriptions can uniquely surface gender biases in ways that require specialized detection and mitigation approaches. Further, we quanti"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2506.05390","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/2506.05390/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":"2026-07-05T11:17:01Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Vo1CbpSZ922O+Y8V/T0saHtdZW/7380oy94Lff3PxGJEo4QD9Hv8AN9FdR0pkTmdrelcMHC747kvgvoHn9YsAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-10T01:44:07.519338Z"},"content_sha256":"5e736b0de67a742fb14f64146e70ef61a9a5df13ed1b26b948695a550ce30fbe","schema_version":"1.0","event_id":"sha256:5e736b0de67a742fb14f64146e70ef61a9a5df13ed1b26b948695a550ce30fbe"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/LSDY74P3UFLKXJVWMO4SGEM5KT/bundle.json","state_url":"https://pith.science/pith/LSDY74P3UFLKXJVWMO4SGEM5KT/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/LSDY74P3UFLKXJVWMO4SGEM5KT/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":"2026-08-10T01:44:07Z","links":{"resolver":"https://pith.science/pith/LSDY74P3UFLKXJVWMO4SGEM5KT","bundle":"https://pith.science/pith/LSDY74P3UFLKXJVWMO4SGEM5KT/bundle.json","state":"https://pith.science/pith/LSDY74P3UFLKXJVWMO4SGEM5KT/state.json","well_known_bundle":"https://pith.science/.well-known/pith/LSDY74P3UFLKXJVWMO4SGEM5KT/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:LSDY74P3UFLKXJVWMO4SGEM5KT","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":"bcc6dee75e309d8fa366b5296726573eabdb8b237a53cf7c9efa889a9a131fdc","cross_cats_sorted":["cs.LG"],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CL","submitted_at":"2025-06-03T18:14:57Z","title_canon_sha256":"c5549c592184c4b69bb382db1bcf37684fb077b13f4d909196f2cb42d9e9542e"},"schema_version":"1.0","source":{"id":"2506.05390","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2506.05390","created_at":"2026-07-05T11:17:01Z"},{"alias_kind":"arxiv_version","alias_value":"2506.05390v1","created_at":"2026-07-05T11:17:01Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2506.05390","created_at":"2026-07-05T11:17:01Z"},{"alias_kind":"pith_short_12","alias_value":"LSDY74P3UFLK","created_at":"2026-07-05T11:17:01Z"},{"alias_kind":"pith_short_16","alias_value":"LSDY74P3UFLKXJVW","created_at":"2026-07-05T11:17:01Z"},{"alias_kind":"pith_short_8","alias_value":"LSDY74P3","created_at":"2026-07-05T11:17:01Z"}],"graph_snapshots":[{"event_id":"sha256:5e736b0de67a742fb14f64146e70ef61a9a5df13ed1b26b948695a550ce30fbe","target":"graph","created_at":"2026-07-05T11:17:01Z","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/2506.05390/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"While gender bias in large language models (LLMs) has been extensively studied in many domains, uses of LLMs in e-commerce remain largely unexamined and may reveal novel forms of algorithmic bias and harm. Our work investigates this space, developing data-driven taxonomic categories of gender bias in the context of product description generation, which we situate with respect to existing general purpose harms taxonomies. We illustrate how AI-generated product descriptions can uniquely surface gender biases in ways that require specialized detection and mitigation approaches. Further, we quanti","authors_text":"Lauren Wilcox, Markelle Kelly, Mohammad Tahaei, Padhraic Smyth","cross_cats":["cs.LG"],"headline":"","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CL","submitted_at":"2025-06-03T18:14:57Z","title":"Understanding Gender Bias in AI-Generated Product Descriptions"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2506.05390","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":"sha256:539e6d2182a8f4dc3aeb78b85b39aef191497688b2033be7fe635f495153660c","target":"record","created_at":"2026-07-05T11:17:01Z","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":"bcc6dee75e309d8fa366b5296726573eabdb8b237a53cf7c9efa889a9a131fdc","cross_cats_sorted":["cs.LG"],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.CL","submitted_at":"2025-06-03T18:14:57Z","title_canon_sha256":"c5549c592184c4b69bb382db1bcf37684fb077b13f4d909196f2cb42d9e9542e"},"schema_version":"1.0","source":{"id":"2506.05390","kind":"arxiv","version":1}},"canonical_sha256":"5c878ff1fba156aba6b663b923119d54f1fbac137578fdcefe367dca8589c94c","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"5c878ff1fba156aba6b663b923119d54f1fbac137578fdcefe367dca8589c94c","first_computed_at":"2026-07-05T11:17:01.868165Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:17:01.868165Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"nFBmg0VGRp2CjxFvOrAK0NjlzqAw4XvJU9fWKlqJbTcF06QzjACnGwhUP9VBqjNxFaQxiHvquG9P1gjgiK2cAQ==","signature_status":"signed_v1","signed_at":"2026-07-05T11:17:01.868626Z","signed_message":"canonical_sha256_bytes"},"source_id":"2506.05390","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:539e6d2182a8f4dc3aeb78b85b39aef191497688b2033be7fe635f495153660c","sha256:5e736b0de67a742fb14f64146e70ef61a9a5df13ed1b26b948695a550ce30fbe"],"state_sha256":"52bd9661de53f105865d5ef90efc4f9a3a22b996678cae83c5d031c6398d49f0"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"NFB9jfcBK6C814OYwVUBN4jHHnahwFFf5j9lRNzU4sQlGzLkR9QVR8Oej7/JR6m/0XZAvERYRHDGS+hA1QECDQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-10T01:44:07.524667Z","bundle_sha256":"453268f42067a63b36aef1c7f227c154bb0da392e4ff912f2e05f9d9dcf74d88"}}