6 papers
OracleTSC: Oracle-Informed Reward Hurdle and Uncertainty Regularization for Traffic Signal Control
Darryl Jacob, Xinyu Liu, Muchao Ye +2
Transparent decision-making is essential for traffic signal control (TSC) systems to earn public trust. However, traditional reinforcement learning-based TSC methods function as bl…
ER-MIA: Black-Box Adversarial Memory Injection Attacks on Long-Term Memory-Augmented Large Language Models
Mitchell Piehl, Zhaohan Xi, Zuobin Xiong +2
Large language models (LLMs) are increasingly augmented with long-term memory systems to overcome finite context windows and enable persistent reasoning across interactions. Howeve…
Understanding Real-World Traffic Safety through RoadSafe365 Benchmark
Xinyu Liu, Darryl C. Jacob, Yuxin Liu +4
Although recent traffic benchmarks have advanced multimodal data analysis, they generally lack systematic evaluation aligned with official safety standards. To fill this gap, we in…
A Simple Framework Towards Vision-based Traffic Signal Control with Microscopic Simulation
Pan He, Quanyi Li, Xiaoyong Yuan +1
Traffic signal control (TSC) is crucial for reducing traffic congestion leading to smoother traffic flow, reduced idle time, and mitigated CO2 emissions. In this paper, we explore…
MOBA: A Material-Oriented Backdoor Attack against LiDAR-based 3D Object Detection Systems
Saket S. Chaturvedi, Gaurav Bagwe, Lan Zhang +2
LiDAR-based 3D object detection is widely used in safety-critical systems. However, these systems remain vulnerable to backdoor attacks that embed hidden malicious behaviors during…
VERA: Explainable Video Anomaly Detection via Verbalized Learning of Vision-Language Models
Muchao Ye, Weiyang Liu, Pan He
The rapid advancement of vision-language models (VLMs) has established a new paradigm in video anomaly detection (VAD): leveraging VLMs to simultaneously detect anomalies and provi…