2 citations · 3 across the 12 of their papers we have counts for
12 papers
DiffSafeMerge: Mitigating Backdoor Inheritance in Diffusion Model Merging
Jiayang Zhang, Ji Guo, Jiachen Li +2
Unconditional diffusion checkpoint merging assumes benign sources, yet a compromised public checkpoint can transfer a dormant backdoor while clean generation appears normal. Mitiga…
CBV: Clean-label Backdoor Attacks on Vision Language Models via Diffusion Models
Ji Guo, Xiaolong Qin, Cencen Liu +3
Vision-Language Models (VLMs) have achieved remarkable success in tasks such as image captioning and visual question answering (VQA). However, as their applications become increasi…
AlignVAR: Towards Globally Consistent Visual Autoregression for Image Super-Resolution
Cencen Liu, Dongyang Zhang, Wen Yin +6
Visual autoregressive (VAR) models have recently emerged as a promising alternative for image generation, offering stable training, non-iterative inference, and high-fidelity synth…
State Backdoor: Towards Stealthy Real-world Poisoning Attack on Vision-Language-Action Model in State Space
Ji Guo, Wenbo Jiang, Yansong Lin +6
Vision-Language-Action (VLA) models are widely deployed in safety-critical embodied AI applications such as robotics. However, their complex multimodal interactions also expose new…
BadDepth: Backdoor Attacks Against Monocular Depth Estimation in the Physical World
Ji Guo, Long Zhou, Zhijin Wang +4
In recent years, deep learning-based Monocular Depth Estimation (MDE) models have been widely applied in fields such as autonomous driving and robotics. However, their vulnerabilit…
BadSR: Stealthy Label Backdoor Attacks on Image Super-Resolution
Ji Guo, Xiaolei Wen, Wenbo Jiang +3
With the widespread application of super-resolution (SR) in various fields, researchers have begun to investigate its security. Previous studies have demonstrated that SR models ca…
Evaluating Robustness of Large Audio Language Models to Audio Injection: An Empirical Study
Guanyu Hou, Jiaming He, Yinhang Zhou +4
Large Audio-Language Models (LALMs) are increasingly deployed in real-world applications, yet their robustness against malicious audio injection attacks remains underexplored. This…
BadRefSR: Backdoor Attacks Against Reference-based Image Super Resolution
Xue Yang, Tao Chen, Lei Guo +4
Reference-based image super-resolution (RefSR) represents a promising advancement in super-resolution (SR). In contrast to single-image super-resolution (SISR), RefSR leverages an…
TrojanEdit: Multimodal Backdoor Attack Against Image Editing Model
Ji Guo, Peihong Chen, Wenbo Jiang +6
Multimodal diffusion models for image editing generate outputs conditioned on both textual instructions and visual inputs, aiming to modify target regions while preserving the rest…
Backdoor Attack Against Vision Transformers via Attention Gradient-Based Image Erosion
Ji Guo, Hongwei Li, Wenbo Jiang +1
Vision Transformers (ViTs) have outperformed traditional Convolutional Neural Networks (CNN) across various computer vision tasks. However, akin to CNN, ViTs are vulnerable to back…
One Prompt to Verify Your Models: Black-Box Text-to-Image Models Verification via Non-Transferable Adversarial Attacks
Ji Guo, Wenbo Jiang, Rui Zhang +2
Recently, various types of Text-to-Image (T2I) models have emerged (such as DALL-E and Stable Diffusion), and showing their advantages in different aspects. Therefore, some third-p…
Backdoor Attacks against Hybrid Classical-Quantum Neural Networks
Ji Guo, Wenbo Jiang, Rui Zhang +3
Hybrid Quantum Neural Networks (HQNNs) represent a promising advancement in Quantum Machine Learning (QML), yet their security has been rarely explored. In this paper, we present t…