180 citations · 951 across the 62 of their papers we have counts for
7 papers · 1 filter
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…
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…
Cross-Lingual Transfer Learning for Statistical Type Inference
Zhiming Li, Xiaofei Xie, Haoliang Li +3
Hitherto statistical type inference systems rely thoroughly on supervised learning approaches, which require laborious manual effort to collect and label large amounts of data. Mos…
AVA: Adversarial Vignetting Attack against Visual Recognition
Binyu Tian, Felix Juefei-Xu, Qing Guo +3
Vignetting is an inherited imaging phenomenon within almost all optical systems, showing as a radial intensity darkening toward the corners of an image. Since it is a common effect…
Independent Reinforcement Learning for Weakly Cooperative Multiagent Traffic Control Problem
Chengwei Zhang, Shan Jin, Wanli Xue +3
The adaptive traffic signal control (ATSC) problem can be modeled as a multiagent cooperative game among urban intersections, where intersections cooperate to optimize their common…
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…
Neuron Coverage-Guided Domain Generalization
Chris Xing Tian, Haoliang Li, Xiaofei Xie +2
This paper focuses on the domain generalization task where domain knowledge is unavailable, and even worse, only samples from a single domain can be utilized during training. Our m…