2 papers
cs.SE2024
The Seeds of the FUTURE Sprout from History: Fuzzing for Unveiling Vulnerabilities in Prospective Deep-Learning Libraries
Zhiyuan Li, Jingzheng Wu, Xiang Ling +3
The widespread application of large language models (LLMs) underscores the importance of deep learning (DL) technologies that rely on foundational DL libraries such as PyTorch and…
cs.SE2024
When Large Language Models Confront Repository-Level Automatic Program Repair: How Well They Done?
Yuxiao Chen, Jingzheng Wu, Xiang Ling +4
In recent years, large language models (LLMs) have demonstrated substantial potential in addressing automatic program repair (APR) tasks. However, the current evaluation of these m…