{"metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00238508","sets":["1164:4179:11560:11760"]},"path":["11760"],"owner":"44499","recid":"238508","title":["k近傍事例を用いたニューラルモデルの予測における定量的な解釈"],"pubdate":{"attribute_name":"公開日","attribute_value":"2024-08-27"},"_buckets":{"deposit":"415ad181-daaf-4705-a1c4-4710eb3a968a"},"_deposit":{"id":"238508","pid":{"type":"depid","value":"238508","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"k近傍事例を用いたニューラルモデルの予測における定量的な解釈","author_link":["653119","653117","653120","653118"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"k近傍事例を用いたニューラルモデルの予測における定量的な解釈"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"LLM応用・言語解析","subitem_subject_scheme":"Other"}]},"item_type_id":"4","publish_date":"2024-08-27","item_4_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"奈良先端科学技術大学院大学"},{"subitem_text_value":"奈良先端科学技術大学院大学"},{"subitem_text_value":"奈良先端科学技術大学院大学"},{"subitem_text_value":"奈良先端科学技術大学院大学"}]},"item_4_text_4":{"attribute_name":"著者所属(英)","attribute_value_mlt":[{"subitem_text_value":"Nara Institute of Science and Technology","subitem_text_language":"en"},{"subitem_text_value":"Nara Institute of Science and Technology","subitem_text_language":"en"},{"subitem_text_value":"Nara Institute of Science and Technology","subitem_text_language":"en"},{"subitem_text_value":"Nara Institute of Science and Technology","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/238508/files/IPSJ-NL24261015.pdf","label":"IPSJ-NL24261015.pdf"},"date":[{"dateType":"Available","dateValue":"2026-08-27"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-NL24261015.pdf","filesize":[{"value":"1.5 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":"23"},{"tax":["include_tax"],"price":"0","billingrole":"44"}],"accessrole":"open_date","version_id":"a88e8409-8897-4758-a090-8208e56390bf","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2024 by the Information Processing Society of Japan"}]},"item_4_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"五藤, 巧"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"出口, 祥之"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"上垣外, 英剛"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"渡辺, 太郎"}],"nameIdentifiers":[{}]}]},"item_4_source_id_9":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AN10115061","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":"2188-8779","subitem_source_identifier_type":"ISSN"}]},"item_4_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"ニューラルモデルにおける予測の解釈は，人間にモデルの改善の指針を与えたり，人間が信頼してモデルを扱う上で重要となる．従来の方法では，特徴量の予測に対する寄与度や，k 近傍事例を目視で分析することで解釈としてきた．しかしながら，人手による定性分析はコストが高く，また，解釈に対して人間の主観によるバイアスが混入する可能性がある．そこで本研究では，解釈ごとにラベルを事前に定義，あるいは用途に応じて追加し，対象とする入力事例と近傍ラベルとの類似度を計算することで，ラベルの確率分布として表現される解釈を提示する．入力文の文法性を判断する容認性判断タスクを対象に，言語学で定義される文法現象や非文法的な要因となる単語の品詞に対応づけて予測の解釈を実施した．また，定量的および定性的な観点の両面から評価実験を行い，提案法が解釈として有用な確率分布を提示できることを明らかにした．","subitem_description_type":"Other"}]},"item_4_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"9","bibliographic_titles":[{"bibliographic_title":"研究報告自然言語処理（NL）"}],"bibliographicPageStart":"1","bibliographicIssueDates":{"bibliographicIssueDate":"2024-08-27","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"15","bibliographicVolumeNumber":"2024-NL-261"}]},"relation_version_is_last":true,"weko_creator_id":"44499"},"updated":"2025-01-19T08:32:45.969247+00:00","created":"2025-01-19T01:41:46.852541+00:00","links":{},"id":238508}