Hugging Face Trending Papers June 10, 2026

Ambient Diffusion Policy: Imitation Learning from Suboptimal Data in Robotics

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We propose Ambient Diffusion Policy, a simple and principled method for imitation learning from suboptimal data in robotics. High-quality, task-specific robot data is expensive and time-consuming to collect, while suboptimal datasets with lower-quality or out-of-distribution demonstrations are abundant.

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arXiv AI

Jun 11

Ambient Diffusion Policy: Imitation Learning from Suboptimal Data in Robotics

arXiv:2606. 12365v1 Announce Type: cross Abstract: We propose Ambient Diffusion Policy, a simple and principled method for imitation learning from suboptimal data in robotics.

By Adam Wei, Nicholas Pfaff, Thomas Cohn, Arif Kerem Day{\i}, Constantinos Daskalakis, Giannis Daras, Russ Tedrake

diffusion robotics data-engineering

arXiv AI

Jun 16

Training and Evaluating Diffusion Policies with Long Context Lengths

arXiv:2606. 16447v1 Announce Type: cross Abstract: Imitation learning has enabled highly-dexterous robotic manipulation from RGB observations.

By Abhinav Agarwal, Adam Wei, Taylan Kargin, Michael Zeng, Cole Becker, Arif Kerem Dayi, Pablo Parrilo, Asuman Ozdaglar, Russ Tedrake

diffusion robotics benchmarks

arXiv Machine Learning

Jun 16

DemoDiffusion: One-Shot Human Imitation using pre-trained Diffusion Policy

arXiv:2506. 20668v3 Announce Type: replace-cross Abstract: We propose DemoDiffusion, a simple method for enabling robots to perform manipulation tasks by imitating a single human demonstration, without requiring task-specific training or paired human-robot data.

By Sungjae Park, Homanga Bharadhwaj, Shubham Tulsiani

diffusion reinforcement-learning robotics

arXiv AI

Jun 16

Sample from What You See: Visuomotor Policy Learning via Diffusion Bridge with Observation-Embedded Stochastic Differential Equation

arXiv:2512. 07212v3 Announce Type: replace Abstract: Imitation learning with diffusion models has advanced robotic control by capturing the multi-modal action distributions.

By Zhaoyang Liu, Mokai Pan, Zhongyi Wang, Kaizhen Zhu, Haotao Lu, Haipeng Zhang, Jingya Wang, Ye Shi

diffusion robotics multimodal benchmarks

arXiv AI

Jun 9

Latent Diffusion Policy: Shaping Latent Spaces for Diffusion-Based Robotic Manipulation

arXiv:2606. 08657v1 Announce Type: cross Abstract: Diffusion-based visuomotor policies operating directly in raw action spaces conflate scene comprehension with trajectory generation within a single denoising process.

By Zhexuan Zhou, Yichen Lai, Jinhao Zhang, Huizhe Li, Youmin Gong, Jie Mei

diffusion robotics

arXiv Machine Learning

Jun 2

Training-Free Imitation Learning with Closed-Form Diffusion Policies

arXiv:2606. 01238v1 Announce Type: cross Abstract: While diffusion-based policies have impressive performance and expressivity, their long offline training slows down the data collection and policy deployment loop.

By Raghav Mishra, Ian R. Manchester

diffusion benchmarks

Related stories

Ambient Diffusion Policy: Imitation Learning from Suboptimal Data in Robotics

Training and Evaluating Diffusion Policies with Long Context Lengths

DemoDiffusion: One-Shot Human Imitation using pre-trained Diffusion Policy

Sample from What You See: Visuomotor Policy Learning via Diffusion Bridge with Observation-Embedded Stochastic Differential Equation

Latent Diffusion Policy: Shaping Latent Spaces for Diffusion-Based Robotic Manipulation

Training-Free Imitation Learning with Closed-Form Diffusion Policies