arXiv Machine Learning June 16, 2026 By Chenxiao Gao, Edward Chen, Tianyi Chen, Bo Dai

FlowRL: A Taxonomy and Modular Framework for Reinforcement Learning with Diffusion Policies

Read the original on arXiv Machine Learning →

arXiv:2603. 27450v2 Announce Type: replace Abstract: Thanks to their remarkable flexibility, diffusion models and flow models have emerged as promising candidates for policy representation.

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arXiv Machine Learning

Jun 2

Mean Flow Policy Optimization

arXiv:2604. 14698v2 Announce Type: replace Abstract: Diffusion models have recently emerged as expressive policy representations for online reinforcement learning (RL).

By Xiaoyi Dong, Xi Sheryl Zhang, Jian Cheng

diffusion reinforcement-learning benchmarks

arXiv AI

Jun 9

Reinforcement Learning for Flow-Matching Policies with Density Transport

arXiv:2606. 08602v1 Announce Type: cross Abstract: We present an online reinforcement learning (RL) algorithm for fine-tuning flow-matching policies in continuous-control problems.

By Boshu Lei, Kostas Daniilidis, Antonio Loquercio

diffusion reinforcement-learning robotics fine-tuning efficiency multimodal safety

arXiv Machine Learning

Sep 15

VGFM: Expressive Robot Policies via Dense Value Guidance in Flow Matching

arXiv:2609.14261v1 Announce Type: cross Abstract: Recent robot learning paradigms increasingly rely on large offline datasets of robotic interactions to train control policies. Expressive generative...

By Prajwal Koirala, Mark Campbell

diffusion reinforcement-learning robotics efficiency multimodal

arXiv Machine Learning

Jun 30

FlowAWR: Online Adaptive Flow Reinforcement via Advantage-Weighted Rectification

arXiv:2606. 30376v1 Announce Type: new Abstract: Aligning generative flow models on continuous spaces via online reinforcement learning is constrained by intractable trajectory likelihoods.

By Zheming Fu, Ruizhe He, Wei Shang, Xiaoxiao Ma, Lei Wang, Chang Liu, Siming Fu

reinforcement-learning safety

arXiv Machine Learning

Jun 2

Lagrangian Perturbation Diffusion Steering: Latent Reinforcement Learning for Generative Policies

arXiv:2606. 01151v1 Announce Type: new Abstract: Behavior cloning with high-capacity generative policies achieves strong imitation performance, but is often limited by demonstration coverage and distribution shift.

By Hikmet Simsir, Ozgur S. Oguz

diffusion reinforcement-learning robotics fine-tuning multimodal benchmarks

arXiv AI

1d ago

Flowing Faster to Coordinate: One-Step Online Multi-Agent Flow Policies

arXiv:2610.01882v1 Announce Type: cross Abstract: Multi-agent reinforcement learning (MARL) provides a powerful framework for learning coordinated behaviors through interactions with the environment....

By Zhuoran Li, Yunzhan Li, Xun Wang, Yihan Du, Longbo Huang

llms agents reinforcement-learning multimodal

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