PerfCoder: Large Language Models for Interpretable Code Performance Optimization

ArXi:2512.14018v2 Announce Type: replace-cross Large language models (LLMs) have achieved remarkable progress in automatic code generation, yet their ability to produce high-performance code remains limited--a critical requirement in real-world software systems. We argue that current LLMs struggle not only due to data scarcity but, importantly, because they lack supervision that guides interpretable and effective performance improvements. In this work, we