Pith. sign in

REVIEW 1 cited by

TRACE: Real-Time Multimodal Common Ground Tracking in Situated Collaborative Dialogues

Not yet reviewed by Pith; the record is open.

Re-run · record.json Download PDF Read on arXiv ↗

This paper has not been read by Pith yet. Machine review is queued; the pith claim, tier, and objections will appear here once it completes.

SPECIMEN: schema-true, not a live event

T0 review · schema-true

One-sentence machine reading of the paper's core claim.

pith:XXXXXXXX · record.json · timestamp

arxiv 2503.09511 v1 pith:HFWBYXM7 submitted 2025-03-12 cs.CL

Hannah VanderHoeven , Brady Bhalla , Ibrahim Khebour , Austin Youngren , Videep Venkatesha , Mariah Bradford , Jack Fitzgerald , Carlos Mabrey
show 6 more authors
Jingxuan Tu Yifan Zhu Kenneth Lai Changsoo Jung James Pustejovsky Nikhil Krishnaswamy
This is my paper · ORCID
classification cs.CL
keywords tracemultimodalcollaborativecommongroundreal-timesituatedtracking
verification ladder T0 review T1 audit T2 compute T3 formal
0 comments
read the original 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.

Discussion (0). Continue with ORCID to comment.

Forward citations

Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Computer Vision for Objects used in Group Work: Challenges and Opportunities

    cs.CV 2025-06 conditional novelty 6.0 of 10

    FiboSB is a new 6D pose dataset for blocks in group work; all four state-of-the-art 6D pose methods failed on it, while a fine-tuned YOLO11-x detector achieved 0.898 mAP50.

Pith tools