**FewStepRL: Fine-tuning Few-step Diffusion Models with Reinforcement Learning**

**FewStepRL: Fine-tuning Few-step Diffusion Models with Reinforcement Learning**

> Reinforcement learning (RL) has become a standard post-training method for diffusion models, but most RL objectives roll out the current policy at every iteration, and with a many-step sampler these rollouts typically dominate the cost of training. Few-step models cut this cost, yet they model an average velocity over an interval, whereas existing RL objectives are built for an instantaneous velocity with a many-step...

**来源信息**
- **来源**：HuggingFace Daily Papers（社区热门论文）
- **分类**：行业
- **发布时间**：2026-11-10 08:00（北京时间）
- **原文**：[打开原文](https://huggingface.co/papers/2611.08240)