1 citations · 2 across the 8 of their papers we have counts for
10 papers
BadAction: Backdoor Attacks on Interactive Video Generation via Action-Guided Triggers
Zhihang Wu, Zhongqi Wang, Jie Zhang +3
Interactive video generation (IVG) models have achieved remarkable progress in producing controllable visual content guided by user-defined actions, yet their security vulnerabilit…
DeepBias: Adaptive In-depth Probing of Social Biases in LVLMs
Anqi Li, Jie Zhang, Zhongqi Wang +4
While Large Vision-Language Models (LVLMs) demonstrate remarkable capabilities, they remain highly susceptible to embedded social biases. Existing bias evaluation protocols predomi…
EntropyScan: Towards Model-level Backdoor Detection in LVLMs via Visual Attention Entropy
Xuanyu Ge, Zhongqi Wang, Jie Zhang +2
Large Vision-Language Models (LVLMs) have demonstrated remarkable capabilities across various tasks, yet they remain vulnerable to backdoor attacks. Existing defense methods predom…
What Makes VLMs Robust? Towards Reconciling Robustness and Accuracy in Vision-Language Models
Sen Nie, Jie Zhang, Zhongqi Wang +3
Achieving adversarial robustness in Vision-Language Models (VLMs) inevitably compromises accuracy on clean data, presenting a long-standing and challenging trade-off. In this work,…
Assimilation Matters: Model-level Backdoor Detection in Vision-Language Pretrained Models
Zhongqi Wang, Jie Zhang, Shiguang Shan +1
Vision-language pretrained models (VLPs) such as CLIP have achieved remarkable success, but are also highly vulnerable to backdoor attacks. Given a model fine-tuned by an untrusted…
Dynamic Attention Analysis for Backdoor Detection in Text-to-Image Diffusion Models
Zhongqi Wang, Jie Zhang, Shiguang Shan +1
Recent studies have revealed that text-to-image diffusion models are vulnerable to backdoor attacks, where attackers implant stealthy textual triggers to manipulate model outputs.…
REVAL: A Comprehension Evaluation on Reliability and Values of Large Vision-Language Models
Jie Zhang, Zheng Yuan, Zhongqi Wang +6
The rapid evolution of Large Vision-Language Models (LVLMs) has highlighted the necessity for comprehensive evaluation frameworks that assess these models across diverse dimensions…
Trigger without Trace: Towards Stealthy Backdoor Attack on Text-to-Image Diffusion Models
Jie Zhang, Zhongqi Wang, Shiguang Shan +1
Backdoor attacks targeting text-to-image diffusion models have advanced rapidly. However, current backdoor samples often exhibit two key abnormalities compared to benign samples: 1…
T2IShield: Defending Against Backdoors on Text-to-Image Diffusion Models
Zhongqi Wang, Jie Zhang, Shiguang Shan +1
While text-to-image diffusion models demonstrate impressive generation capabilities, they also exhibit vulnerability to backdoor attacks, which involve the manipulation of model ou…
CCLAP: Controllable Chinese Landscape Painting Generation via Latent Diffusion Model
Zhongqi Wang, Jie Zhang, Zhilong Ji +2
With the development of deep generative models, recent years have seen great success of Chinese landscape painting generation. However, few works focus on controllable Chinese land…