@inproceedings{ma-etal-2026-adapting,
    title = "Adapting Technical-Service {LLM} Agents with Latent Logic Augmentation, Robust Noise Reduction, and Hybrid Reward Modeling",
    author = "Ma, Junzhuo  and
      Shen, Chenghuang  and
      Yu, Yi  and
      Liu, Xingyan  and
      Gu, Jing  and
      Sun, Hangyi  and
      Hu, Guangquan  and
      Liu, Jianfeng  and
      Liu, Weiting  and
      Mingyue, Pu  and
      Yu, Wang  and
      Xiao, Zhengdong  and
      Xie, Rui  and
      Luo, Longjiu  and
      Wang, Qianrong  and
      Cui, Gurong  and
      Qiao, Honglin  and
      Lu, Wenlian",
    editor = "Atanasova, Pepa  and
      Haffari, Gholamreza  and
      Wang, Minghan",
    booktitle = "Proceedings of the 2026 Conference on Empirical Methods in Natural Language Processing: Industry Track",
    month = oct,
    year = "2026",
    address = "Budapest, Hungary",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2026.emnlp-industry.238/",
    pages = "3987--4022",
    ISBN = "979-8-89176-460-6"
}