@inproceedings{wei-qi-zhe-2025-ccl25,
    title = "{CCL}25-Eval任务7系统报告:基于古典汉语理解的双阶段多域微调解析框架",
    author = "魏祺哲, 魏祺哲",
    editor = "Lin, Hongfei  and
      Li, Bin  and
      Tan, Hongye",
    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-2.31/",
    pages = "261--270",
    abstract = "``古典汉语作为中华传统文化的重要载体,其语言表达高度凝练且语义复杂,给现代大语言模型带来挑战。为提升中文文学语言理解能力,本文提出一种新的解析框架,采用双阶段多域微调训练策略:第一阶段利用指令生成技术获取大量数据集,随后在此数据集上进行稀疏微调,实现基础适应;第二阶段则高质量标注数据上通过冻结参数在不同域精调,提升具体任务表现。实验基于{''}第一届中国文学语言理解评测(争鸣){''}七项任务,此微调框架得到的结果显著优于基线,验证了双阶段多域微调方法的有效性,相关模型已开源于https:/huggingface.co/wqz123/D2Dtest。''"
}