TRACE: Real-Time Multimodal Common Ground Tracking in Situated Collaborative Dialogues
Hannah VanderHoeven, Brady Bhalla, Ibrahim Khebour, Austin C. Youngren, Videep Venkatesha, Mariah Bradford, Jack Fitzgerald, Carlos Mabrey
Abstract
We present TRACE, a novel system for live *common ground* tracking in situated collaborative tasks. With a focus on fast, real-time performance, TRACE tracks the speech, actions, gestures, and visual attention of participants, uses these multimodal inputs to determine the set of task-relevant propositions that have been raised as the dialogue progresses, and tracks the group’s epistemic position and beliefs toward them as the task unfolds. Amid increased interest in AI systems that can mediate collaborations, TRACE represents an important step forward for agents that can engage with multiparty, multimodal discourse.
BibTeX
@inproceedings{vanderhoeven-etal-2025-trace,
title = "{TRACE}: Real-Time Multimodal Common Ground Tracking in Situated Collaborative Dialogues",
author = "VanderHoeven, Hannah and
Bhalla, Brady and
Khebour, Ibrahim and
Youngren, Austin C. and
Venkatesha, Videep and
Bradford, Mariah and
Fitzgerald, Jack and
Mabrey, Carlos and
Tu, Jingxuan and
Zhu, Yifan and
Lai, Kenneth and
Jung, Changsoo and
Pustejovsky, James and
Krishnaswamy, Nikhil",
editor = "Dziri, Nouha and
Ren, Sean (Xiang) and
Diao, Shizhe",
booktitle = "Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies (System Demonstrations)",
month = apr,
year = "2025",
address = "Albuquerque, New Mexico",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2025.naacl-demo.5/",
pages = "40--50",
ISBN = "979-8-89176-191-9"
}