@inproceedings{lin-etal-2025-ccl25,
    title = "{CCL}25-Eval任务10系统报告:面向细粒度中文仇恨言论识别的大语言模型增强",
    author = "Lin, Fanjun  and
      Zhang, Yanwei  and
      Yang, Huang  and
      Yao, Zhiyuan",
    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-2.49/",
    pages = "411--418",
    abstract = "``本文介绍了我们在第二十四届中文计算语言学大会细粒度中文仇恨言论识别任务中的参赛系统。该任务要求构建结构化仇恨四元组(评论对象、论点、目标群体、是否仇恨),提升模型的细粒度检测与可解释性。我们基于大语言模型,首先评估了LoRA参数高效微调效果,优化了超参数配置;其次对标注数据进行结构化处理,增强数据规范性;最后优化提示词设计,引导模型生成准确的结构化输出。实验表明,三阶段优化提升了模型性能。''"
}