Verification Engine

Verification engines are tools designed to formally verify the correctness and safety of complex systems, with a current strong focus on deep neural networks (DNNs). Research emphasizes improving the scalability and accuracy of verification, particularly for DNNs with non-linear activation functions and complex architectures like LSTMs and Vision Transformers, often employing techniques like branch-and-bound and abstraction-refinement. These advancements are crucial for ensuring the reliability of AI systems in safety-critical applications, driving the development of both improved verification algorithms and platforms that integrate multiple verification approaches.