Recent years have seen significant advancements in image restoration, largely attributed to
the development of modern deep neural networks, such as CNNs and Transformers …

While existing backdoor attacks have successfully infected multimodal contrastive learning
models such as CLIP they can be easily countered by specialized backdoor defenses for …

Since the emergence of security concerns in artificial intelligence (AI), there has been
significant attention devoted to the examination of backdoor attacks. Attackers can utilize …

Generative Large Language Models (LLMs) have made significant strides across various
tasks, but they remain vulnerable to backdoor attacks, where specific triggers in the prompt …

Backdoor attacks are commonly executed by contaminating training data, such that a trigger
can activate predetermined harmful effects during the test phase. In this work, we present …

Recently, point clouds have been widely used in computer vision, whereas their collection is
time-consuming and expensive. As such, point cloud datasets are the valuable intellectual …

Recent works on parameter-efficient transfer learning (PETL) show the potential to adapt a
pre-trained Vision Transformer to downstream recognition tasks with only a few learnable …

Multimodal contrastive pretraining, exemplified by models like CLIP, has been found to be
vulnerable to backdoor attacks. While current backdoor defense methods primarily employ …

Despite the exceptional performance of multi-modal large language models (MLLMs), their
deployment requires substantial computational resources. Once malicious users induce …

Multi-modal Large Language Models (MLLMs) have recently achieved enhanced
performance across various vision-language tasks including visual grounding capabilities …