most citedWhat's Wrong with Your Code Generated by Large Language Models? An Extensive Study

6 citations · 7 across the 3 of their papers we have counts for

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cs.SE2026

Don't Regenerate, Debug: A Domain-Specific Agent for Repairing Near-Miss Accelerator Kernels

Yansong Sun, Shenxiu Wu, Siyuan Chen +6

Kernel generation for hardware accelerators such as GPUs and NPUs has become a proving ground for large language models (LLMs), and state-of-the-art systems raise correctness throu…

cs.SE2024★ 1 cited

Multi-Programming Language Sandbox for LLMs

Shihan Dou, Jiazheng Zhang, Jianxiang Zang +25

We introduce MPLSandbox, an out-of-the-box multi-programming language sandbox designed to provide unified and comprehensive feedback from compiler and analysis tools for Large Lang…

cs.SE2024★ 6 cited

What's Wrong with Your Code Generated by Large Language Models? An Extensive Study

Shihan Dou, Haoxiang Jia, Shenxi Wu +14

The increasing development of LLMs in code generation has drawn significant attention among researchers. To enhance LLM-based code generation ability, current efforts are predomina…