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cs.CL2026
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…
cs.CL2026
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…
cs.AI2026
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…