92 citations · 252 across the 14 of their papers we have counts for
5 papers · 1 filter
WheaCha: A Method for Explaining the Predictions of Models of Code
Yu Wang, Ke Wang, Linzhang Wang
Attribution methods have emerged as a popular approach to interpreting model predictions based on the relevance of input features. Although the feature importance ranking can provi…
Sample-Efficient Reinforcement Learning via Counterfactual-Based Data Augmentation
Chaochao Lu, Biwei Huang, Ke Wang +3
Reinforcement learning (RL) algorithms usually require a substantial amount of interaction data and perform well only for specific tasks in a fixed environment. In some scenarios s…
Time-aware Graph Embedding: A temporal smoothness and task-oriented approach
Yonghui Xu, Shengjie Sun, Yuan Miao +6
Knowledge graph embedding, which aims to learn the low-dimensional representations of entities and relationships, has attracted considerable research efforts recently. However, mos…
Testing Neural Program Analyzers
Md Rafiqul Islam Rabin, Ke Wang, Mohammad Amin Alipour
Deep neural networks have been increasingly used in software engineering and program analysis tasks. They usually take a program and make some predictions about it, e.g., bug predi…
COSET: A Benchmark for Evaluating Neural Program Embeddings
Ke Wang, Mihai Christodorescu
Neural program embedding can be helpful in analyzing large software, a task that is challenging for traditional logic-based program analyses due to their limited scalability. A key…