arXiv AI June 2, 2026 By Zemin Yang, Yaoyu He, Yiming Zhong, Yuhao Zhang, Xinge Zhu, Yao Mu, Qingqiu Huang, Yuexin Ma

Implicit Drifting Policy: One-Step Action Generation via Conditional Expert Geometry

arXiv:2606. 01098v1 Announce Type: cross Abstract: Generative action policies based on diffusion or flow matching excel in behavior cloning, yet their iterative sampling is prohibitive for high-frequency robot control.

Summary generated by The Flow from the publisher's feed. The full article lives at arXiv AI.

arXiv Machine Learning

Jul 10

SeFA-Policy: Fast and Accurate Visuomotor Policy Learning with Selective Flow Alignment

arXiv:2511. 08583v2 Announce Type: replace-cross Abstract: Developing efficient and accurate visuomotor policies poses a central challenge in robotic imitation learning.

By Rong Xue, Jiageng Mao, Mingtong Zhang, Yue Wang

diffusion robotics efficiency benchmarks safety

arXiv AI

Jun 11

The Unreasonable Effectiveness of Discrete-Time Gaussian Process Mixtures for Robot Policy Learning

arXiv:2505. 03296v2 Announce Type: replace-cross Abstract: We present Mixture of Discrete-time Gaussian Processes (MiDiGap), a novel approach for flexible policy representation and imitation learning in robot manipulation.

By Jan Ole von Hartz, Adrian R\"ofer, Joschka Boedecker, Abhinav Valada

robotics multimodal benchmarks

arXiv AI

Jun 2

ExpertGen: Scalable Sim-to-Real Expert Policy Learning from Imperfect Behavior Priors

arXiv:2603. 15956v3 Announce Type: replace-cross Abstract: Learning generalizable and robust behavior cloning policies requires large volumes of high-quality robotics data.

By Zifan Xu, Ran Gong, Maria Vittoria Minniti, Kausik Sivakumar, Ahmet Salih Gundogdu, Eric Rosen, Riedana Yan, Tushar Kusnur, Zixing Wang, Di Deng, Peter Stone, Xiaohan Zhang, Karl Schmeckpeper

llms diffusion reinforcement-learning robotics benchmarks

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

Jul 13

ReinforceGen: Hybrid Skill Policies with Automated Data Generation and Reinforcement Learning

arXiv:2512. 16861v2 Announce Type: replace-cross Abstract: Long-horizon manipulation has been a long-standing challenge in the robotics community.

By Zihan Zhou, Animesh Garg, Ajay Mandlekar, Caelan Garrett

reinforcement-learning robotics fine-tuning benchmarks

arXiv Machine Learning

Jul 9

Latent Policy Steering through One-Step Flow Policies

arXiv:2603. 05296v2 Announce Type: replace-cross Abstract: Offline reinforcement learning (RL) allows robots to learn from offline datasets without risky exploration.

By Hokyun Im, Andrey Kolobov, Jianlong Fu, Youngwoon Lee

reinforcement-learning robotics efficiency benchmarks

Related stories

SeFA-Policy: Fast and Accurate Visuomotor Policy Learning with Selective Flow Alignment

The Unreasonable Effectiveness of Discrete-Time Gaussian Process Mixtures for Robot Policy Learning

ExpertGen: Scalable Sim-to-Real Expert Policy Learning from Imperfect Behavior Priors

Lagrangian Perturbation Diffusion Steering: Latent Reinforcement Learning for Generative Policies

ReinforceGen: Hybrid Skill Policies with Automated Data Generation and Reinforcement Learning

Latent Policy Steering through One-Step Flow Policies