FUSE: Quantifying Uncertainty in Vision-Language Models by Bayesian Fusing Epistemic and Aleatoric Uncertainty
Researchers developed FUSE, a Bayesian framework that quantifies aleatoric and epistemic uncertainty in vision-language models, achieving state-of-the-art uncertainty calibration for downstream applications like robotics…