2 citations · 6 across the 35 of their papers we have counts for
6 papers · 1 filter
Verified Lifting of Deep learning Operators
Qi Zhan, Xing Hu, Xin Xia +1
Deep learning operators are fundamental components of modern deep learning frameworks. With the growing demand for customized operators, it has become increasingly common for devel…
SelfPiCo: Self-Guided Partial Code Execution with LLMs
Zhipeng Xue, Zhipeng Gao, Shaohua Wang +3
Code executability plays a vital role in software debugging and testing (e.g., detecting runtime exceptions or assertion violations). However, code execution, especially partial or…
Where Is Self-admitted Code Generated by Large Language Models on GitHub?
Xiao Yu, Lei Liu, Xing Hu +2
The increasing use of Large Language Models (LLMs) in software development has garnered significant attention from researchers evaluating the capabilities and limitations of LLMs f…
Automating TODO-missed Methods Detection and Patching
Zhipeng Gao, Yanqi Su, Xing Hu +1
TODO comments are widely used by developers to remind themselves or others about incomplete tasks. In other words, TODO comments are usually associated with temporary or suboptimal…
Fight Fire with Fire: How Much Can We Trust ChatGPT on Source Code-Related Tasks?
Xiao Yu, Lei Liu, Xing Hu +3
With the increasing utilization of large language models such as ChatGPT during software development, it has become crucial to verify the quality of code content it generates. Rece…
Refactoring Deep Learning Code: A Study of Practices and Unsatisfied Tool Needs
Siqi Wang, Xing Hu, Bei Wang +3
With the rapid development of deep learning, the implementation of intricate algorithms and substantial data processing have become standard elements of deep learning projects. As…