11 papers
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…
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…
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…
Talk2Move: Reinforcement Learning for Text-Instructed Object-Level Geometric Transformation in Scenes
Jing Tan, Zhaoyang Zhang, Yantao Shen +6
We introduce Talk2Move, a reinforcement learning (RL) based diffusion framework for text-instructed spatial transformation of objects within scenes. Spatially manipulating objects…
SS4D: Native 4D Generative Model via Structured Spacetime Latents
Zhibing Li, Mengchen Zhang, Tong Wu +3
We present SS4D, a native 4D generative model that synthesizes dynamic 3D objects directly from monocular video. Unlike prior approaches that construct 4D representations by optimi…
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…