Robotics Research Hub

Diffusion Policy

4 papers

Robot policies using diffusion models for action generation.

sim-to-real reinforcement-learning diffusion-policy manipulation humanoid ar-vr evaluation locomotion

Papers

Sorted by year (newest first)
Flash-WAM: Modality-Aware Distillation for World Action Models

Flash-WAM: Modality-Aware Distillation for World Action Models

Arman Akbari, Ci Zhang, Arash Akbari et al. · arXiv preprint · Jun 2026

World-action models (WAMs) jointly generate future video and robot actions through iterative diffusion, achieving strong performance on manipulation benchmarks but requiring tens of denoising steps, a cost that precludes real-time control. Step distillation has emerged as the natural remedy, but off...

sim-to-real reinforcement-learning diffusion-policy manipulation humanoid
PDF Intermediate
No code repo Jun 2026
Sample-Efficient Diffusion-based Reinforcement Learning with Critic Guidance

Sample-Efficient Diffusion-based Reinforcement Learning with Critic Guidance

Shutong Ding, Zejia Zhong, Zhongyi Wang et al. · ICML 2026 · May 2026

Recent advances in reinforcement learning (RL) have achieved great successes by leveraging the multimodality and exploration capability of diffusion policies. Among these approaches, one representativ

diffusion-policy reinforcement-learning locomotion manipulation
PDF Advanced
No code repo Code updated: May 2026

Suggested Learning Path

Read these papers in order to build expertise in Diffusion Policy.

  1. 1
    Flash-WAM: Modality-Aware Distillation for World Action Models

    Arman Akbari, Ci Zhang et al. · 2026

  2. 2
    Frequency-Aware Flow Matching for Continuous and Consistent Robotic Action Generation

    Jianing Guo, Fangzheng Chen et al. · 2026

  3. 3
    Frequency-Aware Flow Matching for Continuous and Consistent Robotic Action Generation

    Jianing Guo, Fangzheng Chen et al. · 2026

  4. 4
    Sample-Efficient Diffusion-based Reinforcement Learning with Critic Guidance

    Shutong Ding, Zejia Zhong et al. · 2026