3 papers
stat.ML2025
Input Adaptive Bayesian Model Averaging
Yuli Slavutsky, Sebastian Salazar, David M. Blei
This paper studies prediction with multiple candidate models, where the goal is to combine their outputs. This task is especially challenging in heterogeneous settings, where diffe…
stat.ML2025
Quantifying Uncertainty in the Presence of Distribution Shifts
Yuli Slavutsky, David M. Blei
Neural networks make accurate predictions but often fail to provide reliable uncertainty estimates, especially under covariate distribution shifts between training and testing. To…
cs.CL2024
CONTESTS: a Framework for Consistency Testing of Span Probabilities in Language Models
Eitan Wagner, Yuli Slavutsky, Omri Abend
Although language model scores are often treated as probabilities, their reliability as probability estimators has mainly been studied through calibration, overlooking other aspect…