15 citations · 20 across the 4 of their papers we have counts for
7 papers
An Empirical Study of Bugs in Quantum Machine Learning Frameworks
Pengzhan Zhao, Xiongfei Wu, Junjie Luo +2
Quantum computing has emerged as a promising domain for the machine learning (ML) area, offering significant computational advantages over classical counterparts. With the growing…
WELL: Applying Bug Detectors to Bug Localization via Weakly Supervised Learning
Zhuo Li, Huangzhao Zhang, Zhi Jin +1
Bug localization, which is used to help programmers identify the location of bugs in source code, is an essential task in software development. Researchers have already made effort…
Self-Edit: Fault-Aware Code Editor for Code Generation
Kechi Zhang, Zhuo Li, Jia Li +2
Large language models (LLMs) have demonstrated an impressive ability to generate codes on competitive programming tasks. However, with limited sample numbers, LLMs still suffer fro…
ToolCoder: Teach Code Generation Models to use API search tools
Kechi Zhang, Huangzhao Zhang, Ge Li +3
Automatically generating source code from natural language descriptions has been a growing field of research in recent years. However, current large-scale code generation models of…
QChecker: Detecting Bugs in Quantum Programs via Static Analysis
Pengzhan Zhao, Xiongfei Wu, Zhuo Li +1
Static analysis is the process of analyzing software code without executing the software. It can help find bugs and potential problems in software that may only appear at runtime.…
Implant Global and Local Hierarchy Information to Sequence based Code Representation Models
Kechi Zhang, Zhuo Li, Zhi Jin +1
Source code representation with deep learning techniques is an important research field. There have been many studies that learn sequential or structural information for code repre…