@inproceedings{jingshen-etal-2024-readability,
    title = "Readability-guided Idiom-aware Sentence Simplification ({RISS}) for {C}hinese",
    author = "Zhang, Jingshen  and
      Chen, Xinglu  and
      Qiu, Xinying  and
      Wang, Zhimin  and
      Feng, Wenhe",
    editor = "Maosong, Sun  and
      Jiye, Liang  and
      Xianpei, Han  and
      Zhiyuan, Liu  and
      Yulan, He",
    booktitle = "Proceedings of the 23rd Chinese National Conference on Computational Linguistics (Volume 1: Main Conference)",
    month = jul,
    year = "2024",
    address = "Taiyuan, China",
    publisher = "Chinese Information Processing Society of China",
    url = "https://preview.aclanthology.org/author-degibert/2024.ccl-1.92/",
    pages = "1183--1200",
    language = "eng",
    abstract = "``Chinese sentence simplification faces challenges due to the lack of large-scale labeledparallel corpora and the prevalence of idioms. To address these challenges, we pro-pose Readability-guided Idiom-aware Sentence Simplification (RISS), a novel frameworkthat combines data augmentation techniques. RISS introduces two key components: (1)Readability-guided Paraphrase Selection (RPS), a method for mining high-quality sen-tence pairs, and (2) Idiom-aware Simplification (IAS), a model that enhances the compre-hension and simplification of idiomatic expressions. By integrating RPS and IAS usingmulti-stage and multi-task learning strategies, RISS outperforms previous state-of-the-artmethods on two Chinese sentence simplification datasets. Furthermore, RISS achievesadditional improvements when fine-tuned on a small labeled dataset. Our approachdemonstrates the potential for more effective and accessible Chinese text simplification.''"
}