{"id":242201,"updated":"2025-01-19T07:24:43.439469+00:00","links":{},"created":"2025-01-19T01:47:16.082983+00:00","metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00242201","sets":["1164:6757:11881:11882"]},"path":["11882"],"owner":"44499","recid":"242201","title":["大規模言語モデルを用いたデータセット内の主観情報の評価"],"pubdate":{"attribute_name":"公開日","attribute_value":"2025-01-16"},"_buckets":{"deposit":"31ff5cc7-e1d3-4bc8-8bd3-a27f2a9f7071"},"_deposit":{"id":"242201","pid":{"type":"depid","value":"242201","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"大規模言語モデルを用いたデータセット内の主観情報の評価","author_link":["668404","668403","668402","668401"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"大規模言語モデルを用いたデータセット内の主観情報の評価"},{"subitem_title":"Evaluation of Subjective Information in a Dataset Using a Large- Scale Linguistic Model","subitem_title_language":"en"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"自律移動技術とAI応用","subitem_subject_scheme":"Other"}]},"item_type_id":"4","publish_date":"2025-01-16","item_4_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"工学院大学"},{"subitem_text_value":"工学院大学"}]},"item_4_text_4":{"attribute_name":"著者所属(英)","attribute_value_mlt":[{"subitem_text_value":"Kogakuin University","subitem_text_language":"en"},{"subitem_text_value":"Kogakuin University","subitem_text_language":"en"}]},"item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"jpn"}]},"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/242201/files/IPSJ-DCC25039042.pdf","label":"IPSJ-DCC25039042.pdf"},"date":[{"dateType":"Available","dateValue":"2027-01-16"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-DCC25039042.pdf","filesize":[{"value":"1.4 MB"}],"mimetype":"application/pdf","priceinfo":[{"tax":["include_tax"],"price":"660","billingrole":"5"},{"tax":["include_tax"],"price":"330","billingrole":"6"},{"tax":["include_tax"],"price":"0","billingrole":"50"},{"tax":["include_tax"],"price":"0","billingrole":"44"}],"accessrole":"open_date","version_id":"cea344d3-bf04-4750-8135-8bf26e0b0ae2","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2025 by the Information Processing Society of Japan"}]},"item_4_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"小林, 篤弥"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"山口, 実靖"}],"nameIdentifiers":[{}]}]},"item_4_creator_6":{"attribute_name":"著者名(英)","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Atsuya, Kobayashi","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Saneyasu, Yamaguchi","creatorNameLang":"en"}],"nameIdentifiers":[{}]}]},"item_4_source_id_9":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AA12628338","subitem_source_identifier_type":"NCID"}]},"item_4_textarea_12":{"attribute_name":"Notice","attribute_value_mlt":[{"subitem_textarea_value":"SIG Technical Reports are nonrefereed and hence may later appear in any journals, conferences, symposia, etc."}]},"item_resource_type":{"attribute_name":"資源タイプ","attribute_value_mlt":[{"resourceuri":"http://purl.org/coar/resource_type/c_18gh","resourcetype":"technical report"}]},"item_4_source_id_11":{"attribute_name":"ISSN","attribute_value_mlt":[{"subitem_source_identifier":"2188-8868","subitem_source_identifier_type":"ISSN"}]},"item_4_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"近年，OpenAI や Microsoft が大規模言語モデル (LLM) を発表し，特に ChatGPT は自然言語処理 (NLP) の研究を行っていない一般の人々にも利用されている．NLP の分野では，GPT シリーズや Bard のような LLM が多数の成果を挙げている．それに伴い，LLM モデルが内包している知識や生成したテキストを用いた「知識推定」の研究も日々行われてきた．しかし，これら知識推定の研究は主に客観的な知識の調査に焦点をあてており，主観的な知識やその偏りに関する分野の調査は不十分である．本研究では，ローカル環境で動かすことのできるパラメータサイズの大規模言語モデルに新聞記事のデータセットを学習させ，主観情報に関する考察を行う．","subitem_description_type":"Other"}]},"item_4_description_8":{"attribute_name":"論文抄録(英)","attribute_value_mlt":[{"subitem_description":"Recently, OpenAI and Microsoft have released large-scale language models (LLMs), especially ChatGPT, which has been used by the general public not involved in natural language processing (NLP) research. In line with this, research on “knowledge estimation” using the knowledge contained in LLM models and generated text has been conducted on a daily basis. However, these knowledge estimation studies have mainly focused on the investigation of objective knowledge, and there has been insufficient research in the area of subjective knowledge and its biases. In this study, we examine subjective information by training a dataset of newspaper articles on a large-scale language model with a parameter size that can be run in a local environment.","subitem_description_type":"Other"}]},"item_4_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"6","bibliographic_titles":[{"bibliographic_title":"研究報告デジタルコンテンツクリエーション（DCC）"}],"bibliographicPageStart":"1","bibliographicIssueDates":{"bibliographicIssueDate":"2025-01-16","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"42","bibliographicVolumeNumber":"2025-DCC-39"}]},"relation_version_is_last":true,"weko_creator_id":"44499"}}