Abstract The integration of Artificial Intelligence (AI) with the Internet of Things (IoT), known
as the Artificial Intelligence of Things (AIoT), enhances the devices' processing and analysis …

Large language models (LLMs), exemplified by ChatGPT, have gained considerable
attention for their excellent natural language processing capabilities. Nonetheless, these …

Large language models (LLMs) have gained considerable attention for their excellent
natural language processing capabilities. Nonetheless, these LLMs present many …

Bound propagation methods, when combined with branch and bound, are among the most
effective methods to formally verify properties of deep neural networks such as correctness …

Designing neural networks with bounded Lipschitz constant is a promising way to obtain
certifiably robust classifiers against adversarial examples. However, the relevant progress …

Great advances in deep neural networks (DNNs) have led to state-of-the-art performance on
a wide range of tasks. However, recent studies have shown that DNNs are vulnerable to …

To obtain, deterministic guarantees of adversarial robustness, specialized training methods
are used. We propose, SABR, a novel such certified training method, based on the key …

Lipschitz constants are connected to many properties of neural networks, such as
robustness, fairness, and generalization. Existing methods for computing Lipschitz constants …

Training certifiably robust neural networks remains a notoriously hard problem. While
adversarial training optimizes under-approximations of the worst-case loss, which leads to …

With the rapid development of deep learning, AI systems are being used more in complex
and important domains and necessitates the simultaneous fulfillment of multiple constraints …