With the great achievement of vision transformers (ViTs), transformer-based approaches
have become the new paradigm for solving various computer vision tasks. However, recent …

Various transfer attack methods have been proposed to evaluate the robustness of deep
neural networks (DNNs). Although manifesting remarkable performance in generating …

Imperceptibility is one of the crucial requirements for adversarial examples. Previous
adversarial attacks on 3D point cloud recognition suffer from noticeable outliers, resulting in …

Neural Code Completion Tools (NCCTs) have reshaped the field of software engineering,
which are built upon the language modeling technique and can accurately suggest …

Adversarial Defense of deep neural networks have gained significant attention and there
have been active research efforts on model vulnerabilities for attacking such as gradient …

With the advent of Large Language Models (LLMs), generating rule-based data for real-
world applications has become more accessible. Due to the inherent ambiguity of natural …

Vision-language pretraining (VLP) with transformers has demonstrated exceptional
performance across numerous multimodal tasks. However, the adversarial robustness of …

Adversarial attacks pose a severe threat to the accuracy of person re-identification (re-ID)
systems, a critical security technology. Adversarial purification methods are promising …