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cs.AI2026
Can You Trust Your Preference Models? Stackelberg Games for Alignment
Riccardo Formenti, Aditya Agrawal, Vikas Garg
Language models are frequently aligned to human preferences via imperfect evaluators whose errors can be exploited during optimization. We train policies to search for comparisons…
cs.AI2025
Multi-Environment POMDPs: Discrete Model Uncertainty Under Partial Observability
Eline M. Bovy, Caleb Probine, Marnix Suilen +2
Multi-environment POMDPs (ME-POMDPs) extend standard POMDPs with discrete model uncertainty. ME-POMDPs represent a finite set of POMDPs that share the same state, action, and obser…