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cs.AI2026
Learning Heterogeneous Preferences
Shiwali Mohan, Matt Hong, Dule Shu +3
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 meth…
cs.HC2026
Deconstructing Taste: Toward a Human-Centered AI Framework for Modeling Consumer Aesthetic Perceptions
Matthew K. Hong, Joey Li, Alexandre Filipowicz +6
Understanding and modeling consumers' stylistic taste such as "sporty" is crucial for creating designs that truly connect with target audiences. However, capturing taste during the…