UP Breaks RL Exploration-Stability Dilemma in LLM Reasoning

UP introduces Unbounded Positive Asymmetric Optimization to resolve the tension between importance sampling stability and exploration. By relaxing conservative clipping, the method allows LLMs to follow correct but low-confidence reasoning paths during reinforcement learning.