FAME: Formal Abstract Minimal Explanation for Neural Networks

Researchers introduce FAME (Formal Abstract Minimal Explanations), a new method for explaining neural network decisions that scales to large networks while producing smaller explanations. The approach uses abstract interpretation and dedicated perturbation domains to eliminate irrelevant features and converge to minimal explanations more efficiently than existing methods.