{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2024:3B5KTSP3PTLYVURGELCYRRBQVZ","short_pith_number":"pith:3B5KTSP3","schema_version":"1.0","canonical_sha256":"d87aa9c9fb7cd78ad22622c588c430ae791342aab710b0e1b8823ee4d2313059","source":{"kind":"arxiv","id":"2405.05080","version":1},"attestation_state":"computed","paper":{"title":"Concerns on Bias in Large Language Models when Creating Synthetic Personae","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.HC","authors_text":"Helena A. Haxvig","submitted_at":"2024-05-08T14:24:11Z","abstract_excerpt":"This position paper explores the benefits, drawbacks, and ethical considerations of incorporating synthetic personae in HCI research, particularly focusing on the customization challenges beyond the limitations of current Large Language Models (LLMs). These perspectives are derived from the initial results of a sub-study employing vignettes to showcase the existence of bias within black-box LLMs and explore methods for manipulating them. The study aims to establish a foundation for understanding the challenges associated with these models, emphasizing the necessity of thorough testing before u"},"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":"2405.05080","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.HC","submitted_at":"2024-05-08T14:24:11Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"060931d4a02d0c0fd4ca1101225cb1aa3353685ce0e227d5cc781e3046d802e6","abstract_canon_sha256":"89e423342030b1c008805c9bc69074d356634f89be24b476a46ee0da1c87e129"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T08:16:58.202331Z","signature_b64":"5rQWzu1xn6X5uXyld6h13oSnjlwzL0Ac8KN7qtUESywkxNQz1R7BladS5FX3Le+Ray34RejLoZ1CEHGNstjYAw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"d87aa9c9fb7cd78ad22622c588c430ae791342aab710b0e1b8823ee4d2313059","last_reissued_at":"2026-07-05T08:16:58.201924Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T08:16:58.201924Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Concerns on Bias in Large Language Models when Creating Synthetic Personae","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.HC","authors_text":"Helena A. Haxvig","submitted_at":"2024-05-08T14:24:11Z","abstract_excerpt":"This position paper explores the benefits, drawbacks, and ethical considerations of incorporating synthetic personae in HCI research, particularly focusing on the customization challenges beyond the limitations of current Large Language Models (LLMs). These perspectives are derived from the initial results of a sub-study employing vignettes to showcase the existence of bias within black-box LLMs and explore methods for manipulating them. The study aims to establish a foundation for understanding the challenges associated with these models, emphasizing the necessity of thorough testing before u"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2405.05080","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/2405.05080/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":"2405.05080","created_at":"2026-07-05T08:16:58.201981+00:00"},{"alias_kind":"arxiv_version","alias_value":"2405.05080v1","created_at":"2026-07-05T08:16:58.201981+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2405.05080","created_at":"2026-07-05T08:16:58.201981+00:00"},{"alias_kind":"pith_short_12","alias_value":"3B5KTSP3PTLY","created_at":"2026-07-05T08:16:58.201981+00:00"},{"alias_kind":"pith_short_16","alias_value":"3B5KTSP3PTLYVURG","created_at":"2026-07-05T08:16:58.201981+00:00"},{"alias_kind":"pith_short_8","alias_value":"3B5KTSP3","created_at":"2026-07-05T08:16:58.201981+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":1,"internal_anchor_count":1,"sample":[{"citing_arxiv_id":"2505.24539","citing_title":"Localizing Persona Representations in LLMs","ref_index":73,"is_internal_anchor":true}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/3B5KTSP3PTLYVURGELCYRRBQVZ","json":"https://pith.science/pith/3B5KTSP3PTLYVURGELCYRRBQVZ.json","graph_json":"https://pith.science/api/pith-number/3B5KTSP3PTLYVURGELCYRRBQVZ/graph.json","events_json":"https://pith.science/api/pith-number/3B5KTSP3PTLYVURGELCYRRBQVZ/events.json","paper":"https://pith.science/paper/3B5KTSP3"},"agent_actions":{"view_html":"https://pith.science/pith/3B5KTSP3PTLYVURGELCYRRBQVZ","download_json":"https://pith.science/pith/3B5KTSP3PTLYVURGELCYRRBQVZ.json","view_paper":"https://pith.science/paper/3B5KTSP3","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2405.05080&json=true","fetch_graph":"https://pith.science/api/pith-number/3B5KTSP3PTLYVURGELCYRRBQVZ/graph.json","fetch_events":"https://pith.science/api/pith-number/3B5KTSP3PTLYVURGELCYRRBQVZ/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/3B5KTSP3PTLYVURGELCYRRBQVZ/action/timestamp_anchor","attest_storage":"https://pith.science/pith/3B5KTSP3PTLYVURGELCYRRBQVZ/action/storage_attestation","attest_author":"https://pith.science/pith/3B5KTSP3PTLYVURGELCYRRBQVZ/action/author_attestation","sign_citation":"https://pith.science/pith/3B5KTSP3PTLYVURGELCYRRBQVZ/action/citation_signature","submit_replication":"https://pith.science/pith/3B5KTSP3PTLYVURGELCYRRBQVZ/action/replication_record"}},"created_at":"2026-07-05T08:16:58.201981+00:00","updated_at":"2026-07-05T08:16:58.201981+00:00"}