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Generalized Proximal Policy Optimization: Unifying LLM RL Algorithms from the Perspective of Divergence
Reinforcement learning has become the foundational paradigm for enhancing the reasoning capabilities of LLMs. Yet the dominant approach, Proximal Policy Optimization (PPO), relies on a geometrically degenerate clipping proxy that cannot adapt its resistance to policy shifts, leading to premature cli
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