3 papers
cs.SE2026
Demystifying the Silence of Correctness Bugs in PyTorch Compiler
Meiziniu Li, Dongze Li, Jianmeng Liu +1
Performance optimization of AI infrastructure is key to the fast adoption of large language models (LLMs). The PyTorch compiler (torch.compile), a core optimization tool for deep l…
cs.SE2025
What Builds Effective In-Context Examples for Code Generation?
Dongze Li, Songqiang Chen, Jialun Cao +1
In-Context Learning (ICL) has emerged as a promising solution to enhance the code generation capabilities of Large Language Models (LLMs), which incorporates code examples inside t…
cs.SE2025
Enhancing Differential Testing With LLMs For Testing Deep Learning Libraries
Meiziniu Li, Dongze Li, Jianmeng Liu +3
Differential testing offers a promising strategy to alleviate the test oracle problem by comparing the test results between alternative implementations. However, existing different…