591 citations · 1.2k across the 45 of their papers we have counts for
10 papers · 1 filter
ArchRepair: Block-Level Architecture-Oriented Repairing for Deep Neural Networks
Hua Qi, Zhijie Wang, Qing Guo +4
Over the past few years, deep neural networks (DNNs) have achieved tremendous success and have been continuously applied in many application domains. However, during the practical…
PatchCensor: Patch Robustness Certification for Transformers via Exhaustive Testing
Yuheng Huang, Lei Ma, Yuanchun Li
Vision Transformer (ViT) is known to be highly nonlinear like other classical neural networks and could be easily fooled by both natural and adversarial patch perturbations. This l…
When Cyber-Physical Systems Meet AI: A Benchmark, an Evaluation, and a Way Forward
Jiayang Song, Deyun Lyu, Zhenya Zhang +3
Cyber-physical systems (CPS) have been broadly deployed in safety-critical domains, such as automotive systems, avionics, medical devices, etc. In recent years, Artificial Intellig…
GraphSearchNet: Enhancing GNNs via Capturing Global Dependencies for Semantic Code Search
Shangqing Liu, Xiaofei Xie, Jingkai Siow +3
Code search aims to retrieve accurate code snippets based on a natural language query to improve software productivity and quality. With the massive amount of available programs su…
CarveNet: Carving Point-Block for Complex 3D Shape Completion
Qing Guo, Zhijie Wang, Felix Juefei-Xu +4
3D point cloud completion is very challenging because it heavily relies on the accurate understanding of the complex 3D shapes (e.g., high-curvature, concave/convex, and hollowed-o…
Learning to Adversarially Blur Visual Object Tracking
Qing Guo, Ziyi Cheng, Felix Juefei-Xu +4
Motion blur caused by the moving of the object or camera during the exposure can be a key challenge for visual object tracking, affecting tracking accuracy significantly. In this w…
AdvFilter: Predictive Perturbation-aware Filtering against Adversarial Attack via Multi-domain Learning
Yihao Huang, Qing Guo, Felix Juefei-Xu +4
High-level representation-guided pixel denoising and adversarial training are independent solutions to enhance the robustness of CNNs against adversarial attacks by pre-processing…
Automatic Web Testing using Curiosity-Driven Reinforcement Learning
Yan Zheng, Yi Liu, Xiaofei Xie +4
Web testing has long been recognized as a notoriously difficult task. Even nowadays, web testing still heavily relies on manual efforts while automated web testing is far from achi…
To Share, or not to Share Online Event Trend Aggregation Over Bursty Event Streams
Olga Poppe, Chuan Lei, Lei Ma +2
Complex event processing (CEP) systems continuously evaluate large workloads of pattern queries under tight time constraints. Event trend aggregation queries with Kleene patterns a…
A Search-Based Testing Framework for Deep Neural Networks of Source Code Embedding
Maryam Vahdat Pour, Zhuo Li, Lei Ma +1
Over the past few years, deep neural networks (DNNs) have been continuously expanding their real-world applications for source code processing tasks across the software engineering…