3 papers
cs.SE2026
Counterexample Guided Branching via Directional Relaxation Analysis in Complete Neural Network Verification
Jingyang Li, Fu Song, Guoqiang Li
Deep Neural Networks demonstrate exceptional performance but remain vulnerable to adversarial perturbations, necessitating formal verification for safety-critical deployment. To ad…
cs.SE2026
SimCert: Probabilistic Certification for Behavioral Similarity in Deep Neural Network Compression
Jingyang Li, Fu Song, Guoqiang Li
Deploying Deep Neural Networks (DNNs) on resource-constrained embedded systems requires aggressive model compression techniques like quantization and pruning. However, ensuring tha…
cs.LG2024
Training Verification-Friendly Neural Networks via Neuron Behavior Consistency
Zongxin Liu, Zhe Zhao, Fu Song +4
Formal verification provides critical security assurances for neural networks, yet its practical application suffers from the long verification time. This work introduces a novel m…