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Execution time can be transformed into a learnable reward, leading to substantial improvements in code optimization performance in RL settings.
DecompRL enables LLMs to solve complex problems by breaking them down into manageable sub-tasks, achieving a 50x reduction in GPU costs while enhancing solution diversity.
