@inproceedings{c8336b9d35d44beb9ab49cffe64386b6,
title = "利用大型語言模型改寫中文教育文本可讀性:策略與挑戰",
abstract = "Rewriting educational material has long been an important but labor-intensive task. This paper explores the potential of using open-source large language models (LLMs) to rewrite Chinese educational materials for different grade-level readability. The main methodology is zero-shot prompting approaches without any fine-tuning. While LLMs demonstrated excellent performance in rewriting English materials, their effectiveness for Chinese materials was limited. To address this, we proposed and evaluated three strategies: cross-lingual rewriting, specific grade-level targeting, and iterative rewriting. Our findings suggest that these strategies improved the rewriting of Chinese educational materials, though challenges remain. We provide an in-depth analysis of the advantages and limitations of LLMs in educational material rewriting and discuss potential educational applications.",
keywords = "Chinese Readability, English Readability, Large Language Models, Rewriting, Zero-shot Learning",
author = "Hojin Koh and Gu, \{Wan Jun\} and Tseng, \{Hou Chiang\} and Chen, \{Kuan Yu\} and Sung, \{Yao Ting\}",
note = "Publisher Copyright: {\textcopyright} ROCLING 2024.All rights reserved.; 36th Conference on Computational Linguistics and Speech Processing, ROCLING 2024 ; Conference date: 04-11-2024 Through 05-11-2024",
year = "2024",
language = "繁體中文",
series = "Proceedings of the 36th Conference on Computational Linguistics and Speech Processing, ROCLING 2024",
publisher = "The Association for Computational Linguistics and Chinese Language Processing (ACLCLP)",
pages = "1--10",
editor = "Shu-Chuan Tseng and Yu Tsao and Hen-Hsen Huang and Yao-Chung Fan and Chia-Hui Chang",
booktitle = "Proceedings of the 36th Conference on Computational Linguistics and Speech Processing, ROCLING 2024",
}