3 papers
cs.CR2026
Stealthy Multi-Task Adversarial Attacks
Jiacheng Guo, Tianyun Zhang, Lei Li +3
Deep neural networks are highly vulnerable to adversarial perturbations, raising serious safety concerns in the real-world systems. While prior work mainly explores single-task att…
cs.CV2026
DarkDriving: A Real-World Day and Night Aligned Dataset for Autonomous Driving in the Dark Environment
Wuqi Wang, Haochen Yang, Baolu Li +7
The low-light conditions are challenging to the vision-centric perception systems for autonomous driving in the dark environment. In this paper, we propose a new benchmark dataset…
cs.RO2025
A Low-Rank Method for Vision Language Model Hallucination Mitigation in Autonomous Driving
Keke Long, Jiacheng Guo, Tianyun Zhang +2
Vision Language Models (VLMs) are increasingly used in autonomous driving to help understand traffic scenes, but they sometimes produce hallucinations, which are false details not…