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#artificial intelligence Preprint Sep 2026

Learning Heterogeneous Preferences

Learning from human feedback has become a central paradigm for training modern AI systems, where models of human utility are used as reward models in policy learning. Existing methods typically assume a \emph{universal utility} function shared across a population and treat disagreement between annotators as stochastic...

Shiwali Mohan, Matthew K. Hong, Du-Le Shu et al. · 0 citations

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