Optimizing Stochastic Policy Geometry for Few-Step Flow Reinforcement Learning.

arXiv:2610.41949v1 Announce Type: new Abstract: Few-step flow models generate samples through a handful of large denoising transitions. Applying GRPO to such models requires introducing stochasticity into the denoising transitions, and when a single transition