Multimodal Agentic Dialogue Systems for Situated Human-Robot Interaction

Virgile Sucal

Multimodal Agentic Dialogue Systems for Situated Human-Robot Interaction

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Abstract

This position paper presents the integration of dialogue systems into situated robotics, emphasizing the use of contextual information—particularly audiovisual perceptions—to inform dialogue policies. A central objective is the development of interaction policies that dynamically select contextually appropriate actions aligned with the user’s intentions and needs. The works presented in this paper explore proactive decision-making mechanisms in multimodal interaction settings and seek to enhance robotic expressiveness through nonverbal communication cues. Current efforts focus on evaluating and comparing approaches such as agentic workflows and reinforcement learning within a unified framework, aiming to facilitate more consistent and contextually aware human–robot interaction.

Anthology ID:: 2025.yrrsds-1.8
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:: 20–24
Language:
URL:: https://aclanthology.org/2025.yrrsds-1.8/
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Cite (ACL):: Virgile Sucal. 2025. Multimodal Agentic Dialogue Systems for Situated Human-Robot Interaction. In Proceedings of the 21st Workshop of Young Researchers' Roundtable on Spoken Dialogue Systems, pages 20–24, Avignon, France. Association for Computational Linguistics.
Cite (Informal):: Multimodal Agentic Dialogue Systems for Situated Human-Robot Interaction (Sucal, YRRSDS 2025)
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PDF:: https://aclanthology.org/2025.yrrsds-1.8.pdf

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@inproceedings{sucal-2025-multimodal,
    title = "Multimodal Agentic Dialogue Systems for Situated Human-Robot Interaction",
    author = "Sucal, Virgile",
    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-1.8/",
    pages = "20--24",
    abstract = "This position paper presents the integration of dialogue systems into situated robotics, emphasizing the use of contextual information{---}particularly audiovisual perceptions{---}to inform dialogue policies. A central objective is the development of interaction policies that dynamically select contextually appropriate actions aligned with the user{'}s intentions and needs. The works presented in this paper explore proactive decision-making mechanisms in multimodal interaction settings and seek to enhance robotic expressiveness through nonverbal communication cues. Current efforts focus on evaluating and comparing approaches such as agentic workflows and reinforcement learning within a unified framework, aiming to facilitate more consistent and contextually aware human{--}robot interaction."
}

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%0 Conference Proceedings
%T Multimodal Agentic Dialogue Systems for Situated Human-Robot Interaction
%A Sucal, Virgile
%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 sucal-2025-multimodal
%X This position paper presents the integration of dialogue systems into situated robotics, emphasizing the use of contextual information—particularly audiovisual perceptions—to inform dialogue policies. A central objective is the development of interaction policies that dynamically select contextually appropriate actions aligned with the user’s intentions and needs. The works presented in this paper explore proactive decision-making mechanisms in multimodal interaction settings and seek to enhance robotic expressiveness through nonverbal communication cues. Current efforts focus on evaluating and comparing approaches such as agentic workflows and reinforcement learning within a unified framework, aiming to facilitate more consistent and contextually aware human–robot interaction.
%U https://aclanthology.org/2025.yrrsds-1.8/
%P 20-24

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Markdown (Informal)

[Multimodal Agentic Dialogue Systems for Situated Human-Robot Interaction](https://aclanthology.org/2025.yrrsds-1.8/) (Sucal, YRRSDS 2025)

Multimodal Agentic Dialogue Systems for Situated Human-Robot Interaction (Sucal, YRRSDS 2025)

ACL

Virgile Sucal. 2025. Multimodal Agentic Dialogue Systems for Situated Human-Robot Interaction. In Proceedings of the 21st Workshop of Young Researchers' Roundtable on Spoken Dialogue Systems, pages 20–24, Avignon, France. Association for Computational Linguistics.