{"links":{},"id":234135,"metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00234135","sets":["1164:4619:11539:11642"]},"path":["11642"],"owner":"44499","recid":"234135","title":["Fine-tuning Large Language Models for Automatic Font Skeleton Generation: A First Attempt"],"pubdate":{"attribute_name":"公開日","attribute_value":"2024-05-08"},"_buckets":{"deposit":"79d02cda-0074-4847-ba24-2a63c7800cd0"},"_deposit":{"id":"234135","pid":{"type":"depid","value":"234135","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"Fine-tuning Large Language Models for Automatic Font Skeleton Generation: A First Attempt","author_link":["637467","637462","637465","637466","637463","637469","637464","637468"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"Fine-tuning Large Language Models for Automatic Font Skeleton Generation: A First Attempt"},{"subitem_title":"Fine-tuning Large Language Models for Automatic Font Skeleton Generation: A First Attempt","subitem_title_language":"en"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"セッション1(PRMU)","subitem_subject_scheme":"Other"}]},"item_type_id":"4","publish_date":"2024-05-08","item_4_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"Tokyo Institute of Technology"},{"subitem_text_value":"Google Research"},{"subitem_text_value":"Tokyo Institute of Technology"},{"subitem_text_value":"Tokyo Institute of Technology"}]},"item_4_text_4":{"attribute_name":"著者所属(英)","attribute_value_mlt":[{"subitem_text_value":"Tokyo Institute of Technology","subitem_text_language":"en"},{"subitem_text_value":"Google Research","subitem_text_language":"en"},{"subitem_text_value":"Tokyo Institute of Technology","subitem_text_language":"en"},{"subitem_text_value":"Tokyo Institute of Technology","subitem_text_language":"en"}]},"item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"eng"}]},"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/234135/files/IPSJ-CVIM24238004.pdf","label":"IPSJ-CVIM24238004.pdf"},"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-CVIM24238004.pdf","filesize":[{"value":"3.3 MB"}],"mimetype":"application/pdf","priceinfo":[{"tax":["include_tax"],"price":"0","billingrole":"20"},{"tax":["include_tax"],"price":"0","billingrole":"44"}],"accessrole":"open_login","version_id":"a0700bb1-cc3d-4822-a53c-0152fc8c2667","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2024 by the Institute of Electronics, Information and Communication Engineers This SIG report is only available to those in membership of the SIG."}]},"item_4_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Yuxuan, Liu"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Yasuhisa, Fujii"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Xinru, Zhu"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Kayoko, Nohara"}],"nameIdentifiers":[{}]}]},"item_4_creator_6":{"attribute_name":"著者名(英)","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Yuxuan, Liu","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Yasuhisa, Fujii","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Xinru, Zhu","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Kayoko, Nohara","creatorNameLang":"en"}],"nameIdentifiers":[{}]}]},"item_4_source_id_9":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AA11131797","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":"2188-8701","subitem_source_identifier_type":"ISSN"}]},"item_4_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"Despite the pivotal role that font skeletons could play in the typeface research and font design, the availability of font skeleton data is sparse and limited. This research explores the possibility of using Large Language Models (LLMs) to generate font skeleton data based on font outline data. By fine-tuning GPT-3.5 with a dataset of 8,213 font outlines and corresponding skeletons, a preliminary LLM model for font skeleton generation has been achieved. Both quantitative and qualitative evaluations were performed to assess the effectiveness of the fine-tuned model, including Rasterized Pixel Distance, Chamfer Distance and visual analysis. This research has established a foundation for the automatic generation of font skeletons using LLMs, setting the stage for future work on automatic skeleton generation and the wider application of font skeletons in typography.","subitem_description_type":"Other"}]},"item_4_description_8":{"attribute_name":"論文抄録(英)","attribute_value_mlt":[{"subitem_description":"Despite the pivotal role that font skeletons could play in the typeface research and font design, the availability of font skeleton data is sparse and limited. This research explores the possibility of using Large Language Models (LLMs) to generate font skeleton data based on font outline data. By fine-tuning GPT-3.5 with a dataset of 8,213 font outlines and corresponding skeletons, a preliminary LLM model for font skeleton generation has been achieved. Both quantitative and qualitative evaluations were performed to assess the effectiveness of the fine-tuned model, including Rasterized Pixel Distance, Chamfer Distance and visual analysis. This research has established a foundation for the automatic generation of font skeletons using LLMs, setting the stage for future work on automatic skeleton generation and the wider application of font skeletons in typography.","subitem_description_type":"Other"}]},"item_4_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"6","bibliographic_titles":[{"bibliographic_title":"研究報告コンピュータビジョンとイメージメディア（CVIM）"}],"bibliographicPageStart":"1","bibliographicIssueDates":{"bibliographicIssueDate":"2024-05-08","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"4","bibliographicVolumeNumber":"2024-CVIM-238"}]},"relation_version_is_last":true,"weko_creator_id":"44499"},"created":"2025-01-19T01:35:47.895867+00:00","updated":"2025-01-19T09:53:26.003095+00:00"}