RewardUQ: A Unified Framework for Uncertainty-Aware Reward Models

Daniel Yang, Samuel Stante, Florian Redhardt +5

Reward models are central to aligning large language models (LLMs) with human preferences. Yet most approaches rely on pointwise reward estimates that overlook the epistemic uncert…