most citedSWE-Perf: Can Language Models Optimize Code Performance on Real-World Repositories?

1 citations · 1 across the 1 of their papers we have counts for

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2 papers

cs.SE2026★ 1 cited

SWE-Perf: Can Language Models Optimize Code Performance on Real-World Repositories?

Xinyi He, Qian Liu, Mingzhe Du +6

Code performance optimization is paramount in real-world software engineering and critical for production-level systems. While Large Language Models (LLMs) have demonstrated impres…

cs.SE2025

Afterburner: Reinforcement Learning Facilitates Self-Improving Code Efficiency Optimization

Mingzhe Du, Luu Anh Tuan, Yue Liu +6

Large Language Models (LLMs) generate functionally correct solutions but often fall short in code efficiency, a critical bottleneck for real-world deployment. In this paper, we int…