@inproceedings{hashimoto-2025-dialogue,
    title = "Dialogue System using Large Language Model-based Dynamic Slot Generation",
    author = "Hashimoto, Ekai",
    editor = "Whetten, Ryan  and
      Sucal, Virgile  and
      Ngo, Anh  and
      Chalamalasetti, Kranti  and
      Inoue, Koji  and
      Cimino, Gaetano  and
      Yang, Zachary  and
      Zenimoto, Yuki  and
      Rodriguez, Ricardo",
    booktitle = "Proceedings of the 21st Workshop of Young Researchers' Roundtable on Spoken Dialogue Systems",
    month = aug,
    year = "2025",
    address = "Avignon, France",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/corrections-2025-10/2025.yrrsds-1.4/",
    pages = "10--11",
    abstract = "In this position paper, I present my research interests in dialogue systems that elicit user career-related information. My work centres on two aspects. First, I seek to enhance the information-gathering capability of task-oriented systems by using large language models (LLMs) to generate slots dynamically, enabling the system to ask for deeper career details, such as reasons for leaving a job. Second, I propose a method{---}planned for future study{---}that decomposes and recomposes system questions along a ``depth'' axis so that sensitive information can be obtained more naturally. Finally, I discuss the positive and negative implications of combining LLMs with spoken dialogue systems (SDSs) and consider how SDS technology will interact with society."
}