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cs.GT2026
Structure from Strategic Interaction & Uncertainty: Risk Sensitive Games for Robust Preference Learning
Max Horwitz, Jake Gonzales, Eric Mazumdar +1
A growing line of work reframes preference-based fine-tuning of large language models game-theoretically: Nash Learning from Human Feedback (NLHF) recasts the problem as a zero-sum…
cs.GT2025
A Learning Algorithm That Attains the Human Optimum in a Repeated Human-Machine Interaction Game
Jason T. Isa, Lillian J. Ratliff, Samuel A. Burden
When humans interact with learning-based control systems, a common goal is to minimize a cost function known only to the human. For instance, an exoskeleton may adapt its assistanc…