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Marginally Correct Tool Caches Can Reverse Group-Normalized Policy Updates
Tool-result caching reduces repeated execution in agent training, but also couples rollout randomness. We study a two-action model in which independent and shared execution preserve every rollout's conditional reward distribution. Despite this marginal agreement, sharing one stochastic result per gr
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