@inproceedings{liu-etal-2025-nan,
    title = "难度可控的词义辨析选择题自动生成",
    author = "Liu, Tingchao  and
      Wang, Yu  and
      Xun, Endong",
    editor = "Sun, Maosong  and
      Duan, Peiyong  and
      Liu, Zhiyuan  and
      Xu, Ruifeng  and
      Sun, Weiwei",
    booktitle = "Proceedings of the 24th {C}hina National Conference on Computational Linguistics ({CCL} 2025)",
    month = aug,
    year = "2025",
    address = "Jinan, China",
    publisher = "Chinese Information Processing Society of China",
    url = "https://preview.aclanthology.org/ingest-ccl/2025.ccl-1.1/",
    pages = "1--15",
    abstract = "``针对汉语词义辨析选择题的自动生成任务,本文提出一种基于检索增强生成(RAG)技术的智能出题框架。该框架通过构建融合词汇等级、词频与句子长度的多维度难度评估模型,实现习题难度的个性化控制。研究通过整合语言要素知识库与BCC语料库,有效提升语境自然性与干扰项质量,并引入格式校验、逻辑验证与答案唯一性检测的多维校验机制,确保输出题目符合教学规范。实验结果显示,该方法在出题成功率、答案正确率与内容多样性等关键指标上显著优于传统微调模型,展现出良好的教学适配性与应用潜力,为汉语教学智能化提供新的技术路径。''"
}