2021
The Out-of-Distribution Problem in Explainability and Search Methods for Feature Importance Explanations
NeurIPS 2021poster
Feature importance (FI) estimates are a popular form of explanation, and they are commonly created and evaluated by computing the change in model confidence caused by removing certain input features at test time. For example, in the standard Sufficiency metric, only the top-k most important tokens a…