4 papers
PersonalQ: Select, Quantize, and Serve Personalized Diffusion Models for Efficient Inference
Qirui Wang, Qi Guo, Yiding Sun +4
Personalized text-to-image generation lets users fine-tune diffusion models into repositories of concept-specific checkpoints, but serving these repositories efficiently is difficu…
PhysPatch: A Physically Realizable and Transferable Adversarial Patch Attack for Multimodal Large Language Models-based Autonomous Driving Systems
Qi Guo, Xiaojun Jia, Shanmin Pang +5
Multimodal Large Language Models (MLLMs) are becoming integral to autonomous driving (AD) systems due to their strong vision-language reasoning capabilities. However, MLLMs are vul…
EmoAttack: Emotion-to-Image Diffusion Models for Emotional Backdoor Generation
Tianyu Wei, Shanmin Pang, Qi Guo +3
Text-to-image diffusion models can generate realistic images based on textual inputs, enabling users to convey their opinions visually through language. Meanwhile, within language,…
Efficient Generation of Targeted and Transferable Adversarial Examples for Vision-Language Models Via Diffusion Models
Qi Guo, Shanmin Pang, Xiaojun Jia +2
Adversarial attacks, particularly \textbf{targeted} transfer-based attacks, can be used to assess the adversarial robustness of large visual-language models (VLMs), allowing for a…