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        <title>A New Dataset and Empirical Study for Sentence Simplification in Chinese</title>
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    <abstract>Sentence Simplification is a valuable technique that can benefit language learners and children a lot. However, current research focuses more on English sentence simplification. The development of Chinese sentence simplification is relatively slow due to the lack of data. To alleviate this limitation, this paper introduces CSS, a new dataset for assessing sentence simplification in Chinese. We collect manual simplifications from human annotators and perform data analysis to show the difference between English and Chinese sentence simplifications. Furthermore, we test several unsupervised and zero/few-shot learning methods on CSS and analyze the automatic evaluation and human evaluation results. In the end, we explore whether Large Language Models can serve as high-quality Chinese sentence simplification systems by evaluating them on CSS.</abstract>
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%0 Conference Proceedings
%T A New Dataset and Empirical Study for Sentence Simplification in Chinese
%A Yang, Shiping
%A Sun, Renliang
%A Wan, Xiaojun
%Y Rogers, Anna
%Y Boyd-Graber, Jordan
%Y Okazaki, Naoaki
%S Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
%D 2023
%8 July
%I Association for Computational Linguistics
%C Toronto, Canada
%F yang-etal-2023-new
%X Sentence Simplification is a valuable technique that can benefit language learners and children a lot. However, current research focuses more on English sentence simplification. The development of Chinese sentence simplification is relatively slow due to the lack of data. To alleviate this limitation, this paper introduces CSS, a new dataset for assessing sentence simplification in Chinese. We collect manual simplifications from human annotators and perform data analysis to show the difference between English and Chinese sentence simplifications. Furthermore, we test several unsupervised and zero/few-shot learning methods on CSS and analyze the automatic evaluation and human evaluation results. In the end, we explore whether Large Language Models can serve as high-quality Chinese sentence simplification systems by evaluating them on CSS.
%R 10.18653/v1/2023.acl-long.462
%U https://aclanthology.org/2023.acl-long.462/
%U https://doi.org/10.18653/v1/2023.acl-long.462
%P 8306-8321

Markdown (Informal)

[A New Dataset and Empirical Study for Sentence Simplification in Chinese](https://aclanthology.org/2023.acl-long.462/) (Yang et al., ACL 2023)

• A New Dataset and Empirical Study for Sentence Simplification in Chinese (Yang et al., ACL 2023)

ACL

• Shiping Yang, Renliang Sun, and Xiaojun Wan. 2023. A New Dataset and Empirical Study for Sentence Simplification in Chinese. In Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pages 8306–8321, Toronto, Canada. Association for Computational Linguistics.