#post-hoc-methods News & Analysis

Evidential Transformation Network: Turning Pretrained Models into Evidential Models for Post-hoc Uncertainty Estimation

Researchers propose Evidential Transformation Network (ETN), a lightweight post-hoc module that converts pretrained models into evidential models for uncertainty estimation without retraining. ETN operates in logit space using sample-dependent affine transformations and Dirichlet distributions, demonstrating improved uncertainty quantification across vision and language benchmarks with minimal computational overhead.