SWE-RL: Advancing LLM Reasoning via Reinforcement Learning on Open Software Evolution

Exploring foci of: arXiv (Cornell University) SWE-RL: Advancing LLM Reasoning via Reinforcement Learning on Open Software Evolution February 2025 • Yuxiang Wei, Olivier Duchenne, Jade Copet, Quentin Carbonneaux, Lingming Zhang, Daniel Fried, Gabriel Synnaeve, Rishabh Singh, Sida I. Wang The recent DeepSeek-R1 release has demonstrated the immense potential of reinforcement learning (RL) in enhancing the general reasoning capabilities of large language models (LLMs). While DeepSeek-R1 and other follow-up work primarily focus on applying RL to competitive coding and math problems, this paper introduces SWE-RL, the first approach to scale RL-based LLM reasoning for real-world software engineering. Leveraging a lightweight rule-based reward (e.g., the similarity score between ground-truth and LLM-gene… Open Article Page

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