Dialogue System using Large Language Model-based Dynamic Slot Generation

Ekai Hashimoto

Dialogue System using Large Language Model-based Dynamic Slot Generation

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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.

Anthology ID:: 2025.yrrsds-1.4
Volume:: Proceedings of the 21st Workshop of Young Researchers' Roundtable on Spoken Dialogue Systems
Month:: August
Year:: 2025
Address:: Avignon, France
Editors:: Ryan Whetten, Virgile Sucal, Anh Ngo, Kranti Chalamalasetti, Koji Inoue, Gaetano Cimino, Zachary Yang, Yuki Zenimoto, Ricardo Rodriguez
Venue:: YRRSDS
SIG:
Publisher:: Association for Computational Linguistics
Note:
Pages:: 10–11
Language:
URL:: https://aclanthology.org/2025.yrrsds-1.4/
DOI:
Bibkey:
Cite (ACL):: Ekai Hashimoto. 2025. Dialogue System using Large Language Model-based Dynamic Slot Generation. In Proceedings of the 21st Workshop of Young Researchers' Roundtable on Spoken Dialogue Systems, pages 10–11, Avignon, France. Association for Computational Linguistics.
Cite (Informal):: Dialogue System using Large Language Model-based Dynamic Slot Generation (Hashimoto, YRRSDS 2025)
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PDF:: https://aclanthology.org/2025.yrrsds-1.4.pdf

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@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://aclanthology.org/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."
}

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%0 Conference Proceedings
%T Dialogue System using Large Language Model-based Dynamic Slot Generation
%A Hashimoto, Ekai
%Y Whetten, Ryan
%Y Sucal, Virgile
%Y Ngo, Anh
%Y Chalamalasetti, Kranti
%Y Inoue, Koji
%Y Cimino, Gaetano
%Y Yang, Zachary
%Y Zenimoto, Yuki
%Y Rodriguez, Ricardo
%S Proceedings of the 21st Workshop of Young Researchers’ Roundtable on Spoken Dialogue Systems
%D 2025
%8 August
%I Association for Computational Linguistics
%C Avignon, France
%F hashimoto-2025-dialogue
%X 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.
%U https://aclanthology.org/2025.yrrsds-1.4/
%P 10-11

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Markdown (Informal)

[Dialogue System using Large Language Model-based Dynamic Slot Generation](https://aclanthology.org/2025.yrrsds-1.4/) (Hashimoto, YRRSDS 2025)

Dialogue System using Large Language Model-based Dynamic Slot Generation (Hashimoto, YRRSDS 2025)

ACL

Ekai Hashimoto. 2025. Dialogue System using Large Language Model-based Dynamic Slot Generation. In Proceedings of the 21st Workshop of Young Researchers' Roundtable on Spoken Dialogue Systems, pages 10–11, Avignon, France. Association for Computational Linguistics.