Scalable On-Policy Reinforcement Learning via Adaptive Batch Scaling

arXiv:2605. 21557v1 Announce Type: new Abstract: Conventional wisdom holds that large-batch training is fundamentally incompatible with Reinforcement Learning (RL) - beyond a modest threshold, increasing batch sizes typically yields diminishing returns or performance degradation due to the inherent non-stationarity of the data distribution.