Cutting-edge diffusion models produce images with high quality and customizability,
enabling them to be used for commercial art and graphic design purposes. But do diffusion …

Feature visualization has gained significant popularity as an explainability method,
particularly after the influential work by Olah et al. in 2017. Despite its success, its …

Feature visualization has gained substantial popularity, particularly after the influential work
by Olah et al. in 2017, which established it as a crucial tool for explainability. However, its …

Large Generative AI (GAI) models have the unparalleled ability to generate text, images,
audio, and other forms of media that are increasingly indistinguishable from human …

Recent advances in adversarial robustness rely on an abundant set of training data, where
using external or additional datasets has become a common setting. However, in real life …

Despite deep learning (DL) has achieved remarkable progress in various domains, the DL
models are still prone to making mistakes. This issue necessitates effective debugging tools …

Differential privacy (DP) is widely being employed in the industry as a practical standard for
privacy protection. While private training of computer vision or natural language processing …

The success of deep learning models has led to their adaptation and adoption by prominent
video understanding methods. The majority of these approaches encode features in a joint …

The success of deep neural networks has driven numerous research studies and
applications from Euclidean to non-Euclidean data. However, there are increasing concerns …

Large-scale language-vision pre-training models, such as CLIP, have achieved remarkable
text-guided image morphing results by leveraging several unconditional generative models …