Break it Down into BTS: Basic, Tiniest Subword Units for Korean
Nayeon Kim, Jun-Hyung Park, Joon-Young Choi, Eojin Jeon, Youjin Kang, SangKeun Lee
Abstract
We introduce Basic, Tiniest Subword (BTS) units for the Korean language, which are inspired by the invention principle of Hangeul, the Korean writing system. Instead of relying on 51 Korean consonant and vowel letters, we form the letters from BTS units by adding strokes or combining them. To examine the impact of BTS units on Korean language processing, we develop a novel BTSbased word embedding framework that is readily applicable to various models. Our experiments reveal that BTS units significantly improve the performance of Korean word embedding on all intrinsic and extrinsic tasks in our evaluation. In particular, BTS-based word embedding outperforms the state-of-theart Korean word embedding by 11.8% in word analogy. We further investigate the unique advantages provided by BTS units through indepth analysis. Our code is available at https: //github.com/irishev/BTS .
Ask Lune
Ask anything. The answer quotes the paper.
Lune reads all of it and the papers around it, then shows you the passages behind every answer.
Lune answers from
the full paper · 2 top-tier papers that cite it · related work
Free to start. No credit card required.
Cited by top-tier papers2
- CHEF in the Language Kitchen: A Generative Data Augmentation Leveraging Korean Morpheme IngredientsJaehyung Seo, Hyeonseok Moon, Jaewook Lee, Sugyeong Eo et al.EMNLP 2023 · 1 citation
- Polishing Every Facet of the GEM: Testing Linguistic Competence of LLMs and Humans in KoreanSungHo Kim, Nayeon Kim, Taehee Jeon, SangKeun LeeACL 2025
Builds on1
Related papers
- KOMBO: Korean Character Representations Based on the Combination Rules of SubcharactersSungHo Kim, Juhyeong Park, Yeachan Kim, SangKeun LeeACL Findings 2024 · 1 citation
- SCRIPT: A Subcharacter Compositional Representation Injection Module for Korean Pre-Trained Language ModelsSungHo Kim, Juhyeong Park, Eda Atalay, SangKeun LeeACL Findings 2026
- An Ensemble Distillation Framework for Sentence Embeddings with Multilingual Round-Trip TranslationTianyu Zong, Likun ZhangAAAI 2023 · 1 citation
- Beyond Distribution: Investigating Language Models' Understanding of Sino-Korean MorphemesTaehee JeonEMNLP Findings 2025
- Length-aware Byte Pair Encoding for Mitigating Over-segmentation in Korean Machine TranslationJungseob Lee, Hyeonseok Moon, Seungjun Lee, Chanjun Park et al.ACL Findings 2024 · 1 citation
