ProRL: Prolonged Reinforcement Learning Expands Reasoning Boundaries in Large Language Models

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Counters the 'RL only reweights base skills' claim by showing sufficiently prolonged, stabilized RL uncovers new reasoning strategies absent from the base model, including on tasks it initially always failed.