@inproceedings{peng-etal-2025-dlpo,
    title = "{DLPO}: Towards a Robust, Efficient, and Generalizable Prompt Optimization Framework from a Deep-Learning Perspective",
    author = "Peng, Dengyun  and
      Zhou, Yuhang  and
      Chen, Qiguang  and
      Liu, JinHao  and
      Chen, Jingjing  and
      Qin, Libo  and
      Che, Wanxiang",
    editor = "Christodoulopoulos, Christos  and
      Chakraborty, Tanmoy  and
      Rose, Carolyn  and
      Peng, Violet",
    booktitle = "Findings of the Association for Computational Linguistics: EMNLP 2025",
    month = nov,
    year = "2025",
    address = "Suzhou, China",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/author-page-yu-wang-polytechnic/2025.findings-emnlp.441/",
    doi = "10.18653/v1/2025.findings-emnlp.441",
    pages = "8311--8334",
    ISBN = "979-8-89176-335-7"
}