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

SungHo Kim, Juhyeong Park, Eda Atalay, SangKeun Lee


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 SCRIPT, a model-agnostic module that injects subcharacter compositional knowledge into Korean PLMs.SCRIPT allows to enhance subword embeddings with structural granularity, without requiring architectural changes or additional pre-training.As a result, 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 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).
Anthology ID:
2026.findings-acl.104
Volume:
Findings of the Association for Computational Linguistics: ACL 2026
Month:
July
Year:
2026
Address:
San Diego, California, United States
Editors:
Maria Liakata, Viviane P. Moreira, Jiajun Zhang, David Jurgens
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Findings
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Publisher:
Association for Computational Linguistics
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Pages:
2185–2213
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https://preview.aclanthology.org/ingest-acl/2026.findings-acl.104/
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Cite (ACL):
SungHo Kim, Juhyeong Park, Eda Atalay, and SangKeun Lee. 2026. SCRIPT: A Subcharacter Compositional Representation Injection Module for Korean Pre-Trained Language Models. In Findings of the Association for Computational Linguistics: ACL 2026, pages 2185–2213, San Diego, California, United States. Association for Computational Linguistics.
Cite (Informal):
SCRIPT: A Subcharacter Compositional Representation Injection Module for Korean Pre-Trained Language Models (Kim et al., Findings 2026)
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https://preview.aclanthology.org/ingest-acl/2026.findings-acl.104.pdf
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