AutoSpec: Automated Generation of Neural Network Specifications
AutoSpec is a framework that automatically generates and evaluates neural network specifications for learning-augmented systems, particularly in safety-critical domains. It uses a tree-based algorithm to partition the input space and a statistical certification framework to provide accuracy guarantees for each specification. Experiments across four applications show that AutoSpec improves F1 score by up to 53% over human-defined specifications and 73% over the strongest baseline.
Why it matters: This work automates the specification process in neural network verification, addressing a key bottleneck and making formal safety guarantees more practical for learning-augmented systems.
Full story at: arXiv Software Engineering ↗