KOMBO：基于子字符组合规则的韩文字符表示
KOMBO: Korean Character Representations Based on the Combination Rules of Subcharacters
AI总结：
本文提出KOMBO框架，通过引入韩文发明原理来表示字符，提升了韩文NLP任务的性能，平均超越现有最佳模型2.11%。
摘要：
韩文书写系统Hangeul有独特的字符表示方式，严格遵循《洪武jongeum》中的发明原理。然而，现有预训练语言模型（PLMs）忽略了这些原理。本文提出KOMBO框架，首次将Hangeul的发明原理应用于字符表示。实验表明，KOMBO在多种NLP任务中表现优异，平均在五个韩文自然语言理解任务中超越现有最佳模型2.11%。此外，广泛实验表明，该方法适用于理解韩文语言的语义特征。KOMBO展示了使用子字符而非传统子词方法的优越性。代码可在https://github.com/SungHo3268/KOMBO获取。
英文摘要：
The Korean writing system, \textit{Hangeul}, has a unique character representation rigidly following the invention principles recorded in \textit{Hunminjeongeum}.\footnote{\textit{Hunminjeongeum} is a book published in 1446 that describes the principles of invention and usage of \textit{Hangeul}, devised by King Sejong \cite{Hunminjeongeum_Guide}.} However, existing pre-trained language models (PLMs) for Korean have overlooked these principles. In this paper, we introduce a novel framework for Korean PLMs called KOMBO, which firstly brings the invention principles of \textit{Hangeul} to represent character. Our proposed method, KOMBO, exhibits notable experimental proficiency across diverse NLP tasks. In particular, our method outperforms the state-of-the-art Korean PLM by an average of 2.11\% in five Korean natural language understanding tasks. Furthermore, extensive experiments demonstrate that our proposed method is suitable for comprehending the linguistic features of the Korean language. Consequently, we shed light on the superiority of using subcharacters over the typical subword-based approach for Korean PLMs. Our code is available at: [https://github.com/SungHo3268/KOMBO](https://github.com/SungHo3268/KOMBO).
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
