6 papers
From Propositional to Perceptual Asymmetry: Extending Frictive Policy Optimization to Asymmetric Partial Information Dialogue
Yifan Zhu, Kyeongmin Rim, James Pustejovsky
Frictive Policy Optimization (FPO; Pustejovsky et al., 2025) treats friction in collaborative dialogue -- misalignment, misunderstanding, repair -- as an epistemic signal essential…
Frictive Policy Optimization for LLMs: Epistemic Intervention, Risk-Sensitive Control, and Reflective Alignment
James Pustejovsky, Nikhil Krishnaswamy
We propose Frictive Policy Optimization (FPO), a framework for learning language model policies that regulate not only what to say, but when and how to intervene in order to manage…
Distributed Partial Information Puzzles: Examining Common Ground Construction Under Epistemic Asymmetry
Yifan Zhu, Mariah Bradford, Kenneth Lai +4
Establishing common ground, a shared set of beliefs and mutually recognized facts, is fundamental to collaboration, yet remains a challenge for current AI systems, especially in mu…
Dynamic Epistemic Friction in Dialogue
Timothy Obiso, Kenneth Lai, Abhijnan Nath +2
Recent developments in aligning Large Language Models (LLMs) with human preferences have significantly enhanced their utility in human-AI collaborative scenarios. However, such app…
TRACE: Real-Time Multimodal Common Ground Tracking in Situated Collaborative Dialogues
Hannah VanderHoeven, Brady Bhalla, Ibrahim Khebour +11
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, g…
Speech Is Not Enough: Interpreting Nonverbal Indicators of Common Knowledge and Engagement
Derek Palmer, Yifan Zhu, Kenneth Lai +8
Our goal is to develop an AI Partner that can provide support for group problem solving and social dynamics. In multi-party working group environments, multimodal analytics is cruc…