7 papers
SCARCE: Scalable Cascade Analysis for Rare-event Characterisation via Embeddings
Yingjie Wang, Yi Dong, Edmund Lau +3
Rare events govern the safety profile of modern AI systems, yet their probabilities are extremely difficult to estimate: direct Monte Carlo requires prohibitive sample budgets. Sub…
Engineering Reliable Autonomous Systems: Challenges and Solutions
Marie Farrell, Matt Luckcuck, Angelo Ferrando +28
Engineering reliable autonomous systems is an important and growing topic in computer science. As autonomous systems become more prevalent, easy-to-use techniques for building them…
k-Inductive Neural Barrier Certificates for Unknown Nonlinear Dynamics
Ben Wooding, Hongchao Zhang, Taylor T. Johnson +1
While conventional (k=1) discrete-time barrier certificate conditions impose strict safety constraints by requiring the function to be non-increasing at every step, k-inductive bar…
Towards Verified and Targeted Explanations through Formal Methods
Hanchen David Wang, Diego Manzanas Lopez, Preston K. Robinette +3
As deep neural networks are deployed in safety-critical domains such as autonomous driving and medical diagnosis, stakeholders need explanations that are interpretable but also tru…
The 6th International Verification of Neural Networks Competition (VNN-COMP 2025): Summary and Results
Konstantin Kaulen, Tobias Ladner, Stanley Bak +8
This report summarizes the 6th International Verification of Neural Networks Competition (VNN-COMP 2025), held as a part of the 8th International Symposium on AI Verification (SAIV…
Neural Network Verification is a Programming Language Challenge
Lucas C. Cordeiro, Matthew L. Daggitt, Julien Girard-Satabin +8
Neural network verification is a new and rapidly developing field of research. So far, the main priority has been establishing efficient verification algorithms and tools, while pr…