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“Learning to Solve Hard Problems in RL for LLMs by Never Giving Up” This paper makes RL better at hard problems by dynamically shifting sampling compute away from already-solved prompts toward problems the model still struggles to solve. Read more about it: www.alphaxiv.org/abs/2609.13443