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20242026
most citedRoboChallenge: Large-scale Real-robot Evaluation of Embodied Policies

1 citations · 2 across the 8 of their papers we have counts for

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cs.RO2026

Unified Motion Retargeting for Humanoids with Learned Point Cloud Correspondence

Hanyang Cao, Yuetong Fang, Taesoo Kwon +10

Humanoid learning increasingly relies on transforming vast and diverse human motion data into high-quality robot reference trajectories. However, retargeting human motion to humano…

cs.RO2026

Realtime-VLA V2: Learning to Run VLAs Fast, Smooth, and Accurate

Chen Yang, Yucheng Hu, Yunchao Ma +3

In deployment of the VLA models to real-world robotic tasks, execution speed matters. In previous work arXiv:2510.26742 we analyze how to make neural computation of VLAs on GPU fas…

cs.RO2026

Morphology-Consistent Humanoid Interaction through Robot-Centric Video Synthesis

Weisheng Xu, Jian Li, Yi Gu +12

Equipping humanoid robots with versatile interaction skills typically requires either extensive policy training or explicit human-to-robot motion retargeting. However, learning-bas…

cs.RO2026

Spherical Latent Motion Prior for Physics-Based Simulated Humanoid Control

Jing Tan, Weisheng Xu, Xiangrui Jiang +11

Learning motion priors for physics-based humanoid control is an active research topic. Existing approaches mainly include variational autoencoders (VAE) and adversarial motion prio…

cs.RO20251 cited

RoboChallenge: Large-scale Real-robot Evaluation of Embodied Policies

Adina Yakefu, Bin Xie, Chongyang Xu +34

Testing on real machines is indispensable for robotic control algorithms. In the context of learning-based algorithms, especially VLA models, demand for large-scale evaluation, i.e…