5 papers · 1 filter
Validating, Not Sampling: Region-Level Robustness of Vision-Language and Vision-Language-Action Models
Bogdan Aron, Christopher Brix, Benedikt Brückner +3
Vision-language models (VLMs) and vision-language-action models (VLAs) are increasingly deployed in real-world applications. There, a small perturbation to the recorded camera imag…
Certified Training for Convolutional Perturbations
Benedikt Brückner, Alessio Lomuscio
Vision models have been found to be susceptible to perturbations such as motion blur induced at runtime by a shaking camera. This impedes their deployment in critical applications…
Hybrid Robustness Verification for Spatio-Temporal Neural Networks
Sherwin Varghese, Matthew Wicker, Alessio Lomuscio
With AI increasingly deployed in safety-critical systems, providing formal robustness guarantees for the underlying models is essential. Existing verification methods either rely o…
Lipschitz Optimization for Formal Verification of Homographies
Jean-Guillaume Durand, Panagiotis Kouvaros, Maxime Gariel +1
The adoption of vision neural networks in regulated industries requires formal robustness guarantees, especially in safety-critical domains such as healthcare, autonomous vehicles,…
A Robust Out-of-Distribution Detection Framework via Synergistic Smoothing
Maria Stoica, Abdelrahman Hekal, Alessio Lomuscio
Reliable out-of-distribution (OOD) detection is a critical requirement for the safe deployment of machine learning systems. Despite recent progress, state-of-the-art OOD detectors…