A two-stage SFT+RL pipeline trains LLM agents to call compiler-analysis tools and select pass sequences, achieving 8.46% mean IR instruction reduction, but the tool's own contribution is not controlled.
Efficient compiler autotuning via bayesian optimization
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Compiler-R1: Towards Agentic Compiler Auto-tuning with Reinforcement Learning
A two-stage SFT+RL pipeline trains LLM agents to call compiler-analysis tools and select pass sequences, achieving 8.46% mean IR instruction reduction, but the tool's own contribution is not controlled.