16 citations · 16 across the 1 of their papers we have counts for
2 papers
cs.LG2025
Preference learning made easy: Everything should be understood through win rate
Lily H. Zhang, Rajesh Ranganath
Preference learning, or the task of aligning generative models to preference comparison data, has yet to reach the conceptual maturity of classification, density estimation, etc. T…
cs.LG2021★ 16 cited
Understanding Failures in Out-of-Distribution Detection with Deep Generative Models
Lily H. Zhang, Mark Goldstein, Rajesh Ranganath
Deep generative models (DGMs) seem a natural fit for detecting out-of-distribution (OOD) inputs, but such models have been shown to assign higher probabilities or densities to OOD…