Post-hoc explanation methods are gaining popularity for interpreting, understanding, and debugging neural networks. Most analyses using such explain decisions in response to inputs drawn from the test set. However, set may have few examples that trigger some model behaviors, as high-confidence failures or ambiguous classifications. To address these challenges, we introduce a flexible inspection...
