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Flow-Map GRPO: Reinforcement Learning for Few-Step Flow-Map Generators via Anchored Stochastic Composition

arXiv cs.LG · 2026-07-02 Cached

Proposes Flow-Map GRPO, an online RL post-training framework for deterministic few-step flow-map generators, introducing Anchored Stochastic Flow Map Composition (ASFMC) to enable stochastic optimization without altering original model parameterization. Experiments on FLUX-based MeanFlow and sCM show improvement across reward-based, perceptual, and task-level metrics.

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#flow-map

AnyFlow: Any-Step Video Diffusion Model with On-Policy Flow Map Distillation

Hugging Face Daily Papers · 2026-05-13 Cached

AnyFlow introduces a novel any-step video diffusion distillation framework that optimizes full ODE sampling trajectories through flow-map transition learning and backward simulation, achieving performance that matches or surpasses consistency-based counterparts while scaling with sampling step budgets.

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Flow Map Learning via Nongradient Vector Flow [pdf]

Hacker News Top · 2026-04-23 Cached

Proposes a nongradient vector flow method for learning flow maps, likely aimed at improving optical flow or motion estimation tasks.

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