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The predictive divergence mask is proposed, which asks whether the next policy-gradient step will increase or decrease the same divergence used by the trust region, and the resulting masks improve RL training across model scales and precision settings.
Best Practice Critic Optimization (BPCO) is developed, a recipe that combines DPPO, value predictions bounded to the reward range, Monte Carlo value targets, unnormalized policy advantages, and length-adaptive generalized advantage estimation and shows that a carefully designed critic provides a reliable alternative to...
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