3 papers
cs.CV2026
NutVLM: A Self-Adaptive Defense Framework against Full-Dimension Attacks for Vision Language Models in Autonomous Driving
Xiaoxu Peng, Dong Zhou, Jianwen Zhang +3
Vision Language Models (VLMs) have advanced perception in autonomous driving (AD), but they remain vulnerable to adversarial threats. These risks range from localized physical patc…
cs.CL2024
Genshin: General Shield for Natural Language Processing with Large Language Models
Xiao Peng, Tao Liu, Ying Wang
Large language models (LLMs) like ChatGPT, Gemini, or LLaMA have been trending recently, demonstrating considerable advancement and generalizability power in countless domains. How…
eess.IV2023
MAD: Meta Adversarial Defense Benchmark
X. Peng, D. Zhou, G. Sun +2
Adversarial training (AT) is a prominent technique employed by deep learning models to defend against adversarial attacks, and to some extent, enhance model robustness. However, th…