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.