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

Abstract

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.