[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"detail-sidebar-cat-0-en-105":3,"doc-seo-267204-105":59,"doc-detail-267204-en":130},{"code":4,"msg":5,"data":6},0,"success",[7,13,18,23,28,33,38,43,48,51,55],{"id":8,"doc_module":4,"doc_module_name":9,"category_name":10,"show_sort_weight":11,"slug":12},1,"Document","Story & Novel",90,"story-novel",{"id":14,"doc_module":4,"doc_module_name":9,"category_name":15,"show_sort_weight":16,"slug":17},2,"Literature",80,"literature",{"id":19,"doc_module":4,"doc_module_name":9,"category_name":20,"show_sort_weight":21,"slug":22},4,"Exam",70,"exam",{"id":24,"doc_module":4,"doc_module_name":9,"category_name":25,"show_sort_weight":26,"slug":27},5,"Comic",60,"comic",{"id":29,"doc_module":4,"doc_module_name":9,"category_name":30,"show_sort_weight":31,"slug":32},6,"Technology",50,"technology",{"id":34,"doc_module":4,"doc_module_name":9,"category_name":35,"show_sort_weight":36,"slug":37},7,"Healthcare",40,"healthcare",{"id":39,"doc_module":4,"doc_module_name":9,"category_name":40,"show_sort_weight":41,"slug":42},8,"Research & Report",30,"research-report",{"id":44,"doc_module":4,"doc_module_name":9,"category_name":45,"show_sort_weight":46,"slug":47},9,"Religion & Spirituality",20,"religion-spirituality",{"id":46,"doc_module":4,"doc_module_name":9,"category_name":49,"show_sort_weight":46,"slug":50},"World Cup","world-cup",{"id":52,"doc_module":4,"doc_module_name":9,"category_name":53,"show_sort_weight":52,"slug":54},10,"Lifestyle","lifestyle",{"id":56,"doc_module":4,"doc_module_name":9,"category_name":57,"show_sort_weight":24,"slug":58},19,"General","general",{"code":4,"msg":60,"data":61},"ok",{"site_id":62,"language":63,"slug":64,"title":65,"keywords":66,"description":67,"schema_data":68,"social_meta":123,"head_meta":125,"extra_data":127,"updated_unix":129},105,"en","kornat-llm-alignment-benchmark-for-korean-social-values-and-common-knowledge","KorNAT - LLM Alignment Benchmark for Korean Social Values and Common Knowledge","","Large Language Models (LLMs) need country-specific cultural understanding and baseline knowledge for effective deployment. KorNAT introduces National Alignment as a two-part measurement of social value alignment and common knowledge alignment for South Korea. Social value alignment is assessed using ground-truth labels from a large-scale survey of 6,174 Korean participants, while common knowledge alignment is built from Korean textbooks and GED reference materials. The benchmark provides 4K and 6K multiple-choice questions and is produced through statistical sampling and multi-round human review, with evaluation results showing limited model performance against a reference score.",{"@graph":69,"@context":122},[70,84,105],{"@type":71,"itemListElement":72},"BreadcrumbList",[73,77,79,82],{"item":74,"name":75,"@type":76,"position":8},"https://docshare.wps.com","Home","ListItem",{"item":78,"name":9,"@type":76,"position":14},"https://docshare.wps.com/document/",{"item":80,"name":40,"@type":76,"position":81},"https://docshare.wps.com/document/research-report/",3,{"item":83,"name":65,"@type":76,"position":19},"https://docshare.wps.com/document/kornat-llm-alignment-benchmark-for-korean-social-values-and-common-knowledge/267204/",{"url":83,"name":65,"@type":85,"image":86,"author":91,"headline":65,"publisher":94,"fileFormat":97,"inLanguage":63,"description":67,"dateModified":98,"datePublished":99,"encodingFormat":97,"isAccessibleForFree":100,"interactionStatistic":101},"DigitalDocument",{"url":87,"@type":88,"width":89,"height":90},"https://docshare.wps.com/thumbnails/kornat-llm-alignment-benchmark-for-korean-social-values-and-common-knowledge/267204.png","ImageObject",300,407,{"name":92,"@type":93},"Tawan","Person",{"url":74,"name":95,"@type":96},"DocShare","Organization","application/pdf","2026-10-29","2026-09-14",true,{"@type":102,"interactionType":103,"userInteractionCount":52},"InteractionCounter",{"@type":104},"ViewAction",{"@type":106,"mainEntity":107},"FAQPage",[108,114,118],{"name":109,"@type":110,"acceptedAnswer":111},"What does KorNAT measure about an LLM for South Korea?","Question",{"text":112,"@type":113},"KorNAT measures National Alignment through two dimensions: social value alignment and common knowledge alignment.","Answer",{"name":115,"@type":110,"acceptedAnswer":116},"How are ground truth labels obtained for the social value dataset?",{"text":117,"@type":113},"Ground truth labels are derived from a large-scale survey with 6,174 unique Korean participants.",{"name":119,"@type":110,"acceptedAnswer":120},"What materials are used to build the common knowledge dataset?",{"text":121,"@type":113},"The common knowledge questions are constructed based on Korean textbooks and GED reference materials, following the compulsory education curriculum.","https://schema.org",{"og:url":83,"og:type":124,"og:title":65,"og:site_name":95,"og:description":67},"article",{"robots":126,"canonical":83},"index,follow",{"doc_id":128,"site_id":62},267204,1790376576,{"code":4,"msg":5,"data":131},{"doc_id":128,"user_id":132,"nickname":92,"user_avatar":133,"doc_module":4,"category_id":39,"category_name":40,"doc_title":65,"doc_description":67,"doc_content":134,"file_id":135,"file_url":136,"file_type":137,"file_size":138,"view_count":52,"is_deleted":4,"is_public":8,"is_downloadable":8,"audit_status":8,"page_count":139,"language":140,"language_code":63,"site_id":62,"html_lang":63,"table_of_contents":141,"faqs":142,"seo_title":143,"seo_description":67,"update_tm":144,"read_time":145,"preview_page_count":4},2336475104042,"https://ap-avatar.wpscdn.com/avatar/22000c4c32af1715be0?x-image-process=image/resize,m_fixed,w_180,h_180&k=1786537525561427321","KorNAT: LLM Alignment Benchmark for Korean Social Values and Common Knowledge  \nJiyoung Lee 1 * , Minwoo Kim2∗ , Seungho Kim 1 , Junghwan Kim2 Seunghyun Won3 , Hwaran Lee4 , Edward Choi 1  \n1 KAIST AI 2DATUMO Inc. 3 Seoul National University Bundang Hospital 4NAVER AI Lab  \n1 {jiyounglee0523, shokim, [edwardchoi}@kaist.ac.kr](edwardchoi}@kaist.ac.kr)  \n2 {mwkim, [jh.kim}@selectstar.ai](jh.kim}@selectstar.ai 3 shwon0213@gmail.com 4 hwaran.lee@navercorp.com)[ 3](jh.kim}@selectstar.ai 3 shwon0213@gmail.com 4 hwaran.lee@navercorp.com)[ shwon0213@gmail.com](jh.kim}@selectstar.ai 3 shwon0213@gmail.com 4 hwaran.lee@navercorp.com)[ 4](jh.kim}@selectstar.ai 3 shwon0213@gmail.com 4 hwaran.lee@navercorp.com)[ hwaran.lee@navercorp.com](jh.kim}@selectstar.ai 3 shwon0213@gmail.com 4 hwaran.lee@navercorp.com)  \nAbstract  \nFor Large Language Models (LLMs) to be effectively deployed in a specific country, they must possess an understanding of the nation’s culture and basic knowledge. To this end, we introduce National Alignment, which measuresan alignment between an LLM and a targeted country from two aspects: social value alignment and common knowledge alignment. Social value alignment evaluates how well the model understands nation-specific social values, while common knowledge alignment examines how well the model captures basic knowledge related to the nation. We constructed KorNAT, the first benchmark that measures national alignment with South Korea. For the social value dataset, we obtained ground truth labels from a large-scale survey involving 6,174 unique Korean participants. For the common knowledge dataset, we constructed samples based on Korean textbooks and GED reference materials. KorNAT contains 4K and 6K multiplechoice questions for social value and common knowledge, respectively. Our dataset creation process is meticulously designed and based on statistical sampling theory and was refined through multiple rounds of human review. The experiment results of seven LLMs reveal that only a few models met our reference score, indicating a potential for further enhancement. KorNAT has received government approval after passing an assessment conducted by a government-affiliated organization dedicated to evaluating dataset quality. Samples and detailed evaluation protocols of our dataset can be found in [https://huggingface.co/](https://huggingface.co/)[ ](https://huggingface.co/)datasets/datumo/KorNAT.  \n1 Introduction  \nLarge Language Models (LLMs) (Brown et al., 2020 ; Ouyang et al., 2022 ; OpenAI et al., 2023)  \n* Equal Contribution.  \nFigure 1: Translated examples from each alignment dataset. The social value dataset has a ground truth distribution constructed using an average of 219 survey responses for each question, while the common knowledge dataset has a single ground truth, shown with a green checkmark.  \nhave attracted global attention due to their impressive performance and their ease of access for worldwide users. Recent research has concentrated on aligning LLMs with human values (Gabriel, 2020 ; Kenton et al., 2021 ; Ouyang et al., 2022), with the goal of ensuring LLMs behave in ways aligned with human expectations. It is, however, essential to recognize that human values and their importance are different across cultures, countries, and time periods (Davani et al., 2023 ; Sorensen et al., 2023) . Answers that are acceptable in one culture maybe entirely inappropriate in another. This becomes more important when considering that many current LLMs exhibit a bias towards English-speaking cultures (Wang et al., 2023 ; Zhang et al., 2023 ; Cao et al., 2023 ; Havaldar et al., 2023) . Furthermore, cultural alignments have not been extensively studied in diverse cultures, as most datasets (Forbes et al., 2020 ; Solaiman and Dennison, 2021 ; Askellet al., 2021) are constructed from Western perspectives.  \n11177  \nFindings of the Association for Computational Linguistics: ACL 2024 , pages 11177–11213 August 11-16, 2024 ©2024 Ass","cbCaimtrPvpO029U","https://ap.wps.com/l/cbCaimtrPvpO029U","pdf",4494891,37,"English","# Introduction\n## National Alignment\n## KorNAT Benchmark Design\n## Dataset Construction and Evaluation","[{\"question\":\"What does KorNAT measure about an LLM for South Korea?\",\"answer\":\"KorNAT measures National Alignment through two dimensions: social value alignment and common knowledge alignment.\"},{\"question\":\"How are ground truth labels obtained for the social value dataset?\",\"answer\":\"Ground truth labels are derived from a large-scale survey with 6,174 unique Korean participants.\"},{\"question\":\"What materials are used to build the common knowledge dataset?\",\"answer\":\"The common knowledge questions are constructed based on Korean textbooks and GED reference materials, following the compulsory education curriculum.\"}]","KorNAT - LLM Alignment Benchmark for Korean Social Values and Common Knowledge | PDF",1789415986,93]