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cs.RO2026

Xiaomi-Robotics-U0: Unified Embodied Synthesis with World Foundation Model

Xinghang Li, Jun Guo, Qiwei Li +21

The paper introduces Xiaomi-Robotics-U0, a 38‑billion‑parameter multimodal autoregressive model that extends foundation image and video generation to embodied robotics, enabling co…

cs.RO2026

Revisiting Embodied Chain-of-Thought for Generalizable Robot Manipulation

Nan Sun, Yuan Zhang, Yongkun Yang +10

Embodied chain-of-thought (CoT) aims to bridge linguistic reasoning and robotic control, but its effective form and integration strategy remain underexplored. In this paper, we rev…

cs.RO2026

RotVLA: Rotational Latent Action for Vision-Language-Action Model

Qiwei Li, Xicheng Gong, Xinghang Li +5

Latent Action Models (LAMs) have emerged as an effective paradigm for handling heterogeneous datasets during Vision-Language-Action (VLA) model pretraining, offering a unified acti…

cs.RO2026

Unified 4D World Action Modeling from Video Priors with Asynchronous Denoising

Jun Guo, Qiwei Li, Peiyan Li +7

We propose X-WAM, a Unified 4D World Model that unifies real-time robotic action execution and high-fidelity 4D world synthesis (video + 3D reconstruction) in a single framework, a…

cs.RO2026

SpatialVAM:Spatial-Aware Multi-View Video Diffusion as a Data-Efficient Robot Policy

Peiyan Li, Yixiang Chen, Yuan Xu +13

Robotic manipulation requires understanding both the 3D spatial structure of the environment and its temporal evolution, yet most existing policies neglect one or both aspects. The…

cs.RO2026

What Matters in Building Vision-Language-Action Models for Generalist Robots

Xinghang Li, Peiyan Li, Long Qian +10

To utilize Foundation Vision Language Models (VLMs) for robotic tasks and motion planning, the community has proposed different methods for injecting action components into VLMs an…