FAME or Fortune? How Formal Explanations Finally Scale to Real Neural Networks
Audit is a boring word until the model says something expensive. A credit model rejects an applicant. A visual inspection model flags a component. A traffic-sign classifier keeps its prediction under small pixel changes. The business question is not merely, “What did the model look at?” That is the demo-room version. The operational question is harder: which input features must remain fixed so that the model’s decision is guaranteed not to change under allowed perturbations? ...