@inproceedings{qianwen-etal-2024-ji,
    title = "基于大模型数据增强的作文流畅性评价方法",
    author = "Qianwen, Peng  and
      Yanzipeng, Gao  and
      Xiaoqing, Li  and
      Fanke, Min  and
      Mingrui, Li  and
      Zhichun, Wang  and
      Tianyun, Liu",
    editor = "Lin, Hongfei  and
      Tan, Hongye  and
      Li, Bin",
    booktitle = "Proceedings of the 23rd Chinese National Conference on Computational Linguistics (Volume 3: Evaluations)",
    month = jul,
    year = "2024",
    address = "Taiyuan, China",
    publisher = "Chinese Information Processing Society of China",
    url = "https://preview.aclanthology.org/fix-sig-urls/2024.ccl-3.33/",
    pages = "294--301",
    language = "zho",
    abstract = "``CCL2024-Eval任 务7为 中 小 学 生 作 文 流 畅 性 评 价 (Chinese Essay Fluency Evalua-tion,CEFE),该任务定义了三项重要且富有挑战性的问题,包括中小学作文病句类型识别、中小学作文病句改写、以及中小学作文流畅性评级。本队伍参加了评测任务7的三项子任务,分别获得了45.19、43.90和45.84的得分。本报告详细介绍本队伍在三个子任务上采用的技术方法,并对评测结果进行分析。''"
}