2 citations · 2 across the 6 of their papers we have counts for
4 papers · 1 filter
UniAda: Universal Adaptive Multi-objective Adversarial Attack for End-to-End Autonomous Driving Systems
Jingyu Zhang, Jacky Wai Keung, Yan Xiao +3
Adversarial attacks play a pivotal role in testing and improving the reliability of deep learning (DL) systems. Existing literature has demonstrated that subtle perturbations to th…
Empirical Insights of Test Selection Metrics under Multiple Testing Objectives and Distribution Shifts
Jingyu Zhang, Fan Wang, Jacky Keung +3
Deep learning (DL)-based systems can exhibit unexpected behavior when exposed to out-of-distribution (OOD) scenarios, posing serious risks in safety-critical domains such as malwar…
FedLAD: A Modular and Adaptive Testbed for Federated Log Anomaly Detection
Yihan Liao, Jacky Keung, Zhenyu Mao +2
Log-based anomaly detection (LAD) is critical for ensuring the reliability of large-scale distributed systems. However, most existing LAD approaches assume centralized training, wh…
Delving into Parameter-Efficient Fine-Tuning in Code Change Learning: An Empirical Study
Shuo Liu, Jacky Keung, Zhen Yang +3
Compared to Full-Model Fine-Tuning (FMFT), Parameter Efficient Fine-Tuning (PEFT) has demonstrated superior performance and lower computational overhead in several code understandi…