Wei Le — accepted AI-conference papers

2026

CodeSense: a Real-World Benchmark and Dataset for Code Semantic Reasoning

Monoshi Kumar Roy, Simin Chen, Benjamin Steenhoek, Jinjun Peng, Gail Kaiser, Baishakhi Ray +1

ICLR 2026poster

Understanding and reasoning about code semantics is essential for enhancing code LLMs' abilities to solve real-world software engineering (SE) tasks. Although several code reasoning benchmarks exist, most rely on synthetic datasets or educational coding problems and focus on coarse-grained reasoning…

Cited by 0 Source ↗code ↗Scholar ↗

2021

RNNRepair: Automatic RNN Repair via Model-based Analysis

Xiaofei Xie, Wenbo Guo, Lei Ma, Wei Le, Jian Wang, Lingjun Zhou +2

ICML 2021spotlight

Deep neural networks are vulnerable to adversarial attacks. Due to their black-box nature, it is rather challenging to interpret and properly repair these incorrect behaviors. This paper focuses on interpreting and repairing the incorrect behaviors of Recurrent Neural Networks (RNNs). We propose a l…

Cited by 25 Source ↗PDF ↗Scholar ↗