{"links":{},"id":2008780,"metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:02008780","sets":["6164:6165:6462:1754030301959"]},"path":["1754030301959"],"owner":"11","recid":"2008780","title":["LLMにおける個人特性に基づくステレオタイプの定量的分析手法の提案"],"pubdate":{"attribute_name":"PubDate","attribute_value":"2025-10-20"},"_buckets":{"deposit":"b5cf5017-1ead-47a2-877f-e01bf4f21faf"},"_deposit":{"id":"2008780","pid":{"type":"depid","value":"2008780","revision_id":0},"owners":[11],"status":"published","created_by":11},"item_title":"LLMにおける個人特性に基づくステレオタイプの定量的分析手法の提案","author_link":[],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"LLMにおける個人特性に基づくステレオタイプの定量的分析手法の提案","subitem_title_language":"ja"},{"subitem_title":"Towards Quantifying Individual-Attribute-Based Stereotypes in LLMs","subitem_title_language":"en"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject_scheme":"Other"}]},"item_type_id":"18","publish_date":"2025-10-20","item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"jpn"}]},"item_18_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"NTT社会情報研究所"},{"subitem_text_value":"NTT社会情報研究所"}]},"item_18_text_4":{"attribute_name":"著者所属(英)","attribute_value_mlt":[{"subitem_text_value":"NTT Social Informatics Laboratories"},{"subitem_text_value":"NTT Social Informatics Laboratories"}]},"item_publisher":{"attribute_name":"出版者","attribute_value_mlt":[{"subitem_publisher":"情報処理学会","subitem_publisher_language":"ja"}]},"publish_status":"0","weko_shared_id":-1,"item_file_price":{"attribute_name":"Billing file","attribute_type":"file","attribute_value_mlt":[{"url":{"url":"https://ipsj.ixsq.nii.ac.jp/record/2008780/files/IPSJ-CSS2025009.pdf","label":"IPSJ-CSS2025009.pdf"},"date":[{"dateType":"Available","dateValue":"2027-10-20"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-CSS2025009.pdf","filesize":[{"value":"725.5 KB"}],"mimetype":"application/pdf","priceinfo":[{"tax":["include_tax"],"price":"660","billingrole":"5"},{"tax":["include_tax"],"price":"330","billingrole":"6"},{"tax":["include_tax"],"price":"0","billingrole":"30"},{"tax":["include_tax"],"price":"0","billingrole":"46"},{"tax":["include_tax"],"price":"0","billingrole":"44"}],"accessrole":"open_date","version_id":"aa982e0f-7989-4585-b9a0-5395a21a5524","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2025 by the Information Processing Society of Japan"}]},"item_18_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"青島,達大"}]},{"creatorNames":[{"creatorName":"秋山,満昭"}]}]},"item_18_creator_6":{"attribute_name":"著者名(英)","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Tatsuhiro Aoshima"}]},{"creatorNames":[{"creatorName":"Mitsuaki Akiyama"}]}]},"item_resource_type":{"attribute_name":"資源タイプ","attribute_value_mlt":[{"resourceuri":"http://purl.org/coar/resource_type/c_5794","resourcetype":"conference paper"}]},"item_18_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"LLM の出力が人々の行動や社会活動へ影響を与える場面が増加している．特に，年齢，性別，人種等の個人特性による影響として，そのステレオタイプを評価することは重要である．\r\n本論文では，個人特性が質問文に含まれる明示的な評価として，その選択肢は「はい」か「いいえ」の二択となるが，その正解に関する解釈が分かれるような状況を想定する．既存研究では，線形な統計モデルを当てはめ，その回帰係数を平均化した結果も報告されているが，例えば，年齢による非線形な変化を見逃す可能性や，人種ごとの異なる方向への偏りを過小評価する可能性がある．そこで我々は，個人特性の変化による応答傾向の差や一致度合いを測るための評価手法を提案し，9 個の LLM を 70 種類の質問で評価した結果を報告する．最後に，LLM の信頼性評価として，各ステークホルダーが実施すべきことについて議論する．","subitem_description_type":"Other"}]},"item_18_description_8":{"attribute_name":"論文抄録(英)","attribute_value_mlt":[{"subitem_description":"As large language models (LLMs) increasingly influence human behavior and social activities, it becomes crucial to assess how individual attributes, such as age, gender, and race, affect their outputs.\r\nThis paper focuses on quantifying stereotypes that arise when explicit evaluations involving individual attributes are embedded in input prompts.\r\nWe focus on yes/no questions that explicitly include individual attributes, where no universally accepted correct answer exists, and interpretations may vary from person to person.\r\nWhile previous studies have employed linear statistical models and averaged regression coefficients, such approaches may overlook non-linear effects of age, and underestimate divergent biases across racial groups.\r\nTo address these limitations, we propose an evaluation method that measures differences and consistencies in response patterns as individual attributes vary.\r\nWe apply our methodology to evaluate nine LLMs across 70 distinct questions.\r\nFinally, we discuss the implications of our findings for trustworthiness evaluations and outline key responsibilities for relevant stakeholders.","subitem_description_type":"Other"}]},"item_18_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"67","bibliographic_titles":[{"bibliographic_title":"コンピュータセキュリティシンポジウム2025論文集"}],"bibliographicPageStart":"60","bibliographicIssueDates":{"bibliographicIssueDate":"2025-10-20","bibliographicIssueDateType":"Issued"}}]},"relation_version_is_last":true,"weko_creator_id":"11"},"created":"2026-03-25T04:52:53.993754+00:00","updated":"2026-03-26T04:35:56.073010+00:00"}