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ACL 2026aclfindings

SCRIPT: A Subcharacter Compositional Representation Injection Module for Korean Pre-Trained Language Models

SungHo Kim, Juhyeong Park, Eda Atalay, SangKeun Lee

Korea University

PDF 由论文原始站点提供,PaperCompass 不保存论文文件。DOI 10.18653/v1/2026.findings-acl.104 ↗

摘要

Korean is a morphologically rich language with a featural writing system in which each character is systematically composed of subcharacter units known as Jamo. These subcharacters not only determine the visual structure of Korean but also encode frequent and linguistically meaningful morphophonological processes. However, most current Korean language models (LMs) are based on subword tokenization schemes, which are not explicitly designed to capture the internal compositional structure of characters. To address this limitation, we propose \textbf{SCRIPT}, a model-agnostic module that injects subcharacter compositional knowledge into Korean PLMs.\textbf{SCRIPT} allows to enhance subword embeddings with structural granularity, without requiring architectural changes or additional pre-training.As a result, \textbf{SCRIPT} consistently enhances all baselines across various Korean natural language understanding (NLU) and generation (NLG) tasks. Moreover, beyond performance gains, detailed linguistic analyses show that \textbf{SCRIPT} reshapes the embedding space in a way that better captures grammatical regularities and semantically cohesive variations. Our code is available at [https://github.com/SungHo3268/SCRIPT](https://github.com/SungHo3268/SCRIPT).