5 citations · 5 across the 3 of their papers we have counts for
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cs.SE2025
Tuning LLM-based Code Optimization via Meta-Prompting: An Industrial Perspective
Jingzhi Gong, Rafail Giavrimis, Paul Brookes +8
There is a growing interest in leveraging multiple large language models (LLMs) for automated code optimization. However, industrial platforms deploying multiple LLMs face a critic…
cs.SE2025★ 5 cited
Language Models for Code Optimization: Survey, Challenges and Future Directions
Jingzhi Gong, Vardan Voskanyan, Paul Brookes +7
Language models (LMs) built upon deep neural networks (DNNs) have recently demonstrated breakthrough effectiveness in software engineering tasks such as code generation, completion…