5 citations · 5 across the 9 of their papers we have counts for
10 papers
SplineWAM: Adaptive Action Horizons for World Action Models via B-Spline Representations
Jun Guo, Xiaoshen Han, Qiwei Li +7
World action models (WAMs) are large embodied policies that jointly predict future video and the actions to execute, emitting a fixed-length action chunk per inference call. Such a…
4D-WAM: Infusing Spatiotemporal Awareness into World Action Models through Trajectory Fields
Lishan Yang, Wenxuan Song, Xi Wang +14
Building on recent advances in world models, World Action Models (WAMs) jointly model video prediction and action generation. However, they typically represent videos in 2D pixel s…
Xiaomi-Robotics-1: Scaling Vision-Language-Action Models with over 100K Hours of Real-World Trajectories
Xiaomi Robotics Team, Jun Guo, Piaopiao Jin +31
We present Xiaomi-Robotics-1, a foundational vision-language-action (VLA) model capable of (1) following diverse language instructions to perform a wide range of mobile manipulatio…
Xiaomi-Robotics-U0: Unified Embodied Synthesis with World Foundation Model
Xinghang Li, Jun Guo, Qiwei Li +21
Recent foundation image and video generation models offer strong generalization and controllability, but their direct application to embodied scenarios is limited by requirements f…
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 with robotic control, yet its effective form and integration remain underexplored. In this paper, we revisit emb…
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…
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…
Transforming Monolithic Foundation Models into Embodied Multi-Agent Architectures for Human-Robot Collaboration
Nan Sun, Bo Mao, Yongchang Li +3
Foundation models have become central to unifying perception and planning in robotics, yet real-world deployment exposes a mismatch between their monolithic assumption that a singl…
CollabVLA: Self-Reflective Vision-Language-Action Model Dreaming Together with Human
Nan Sun, Yongchang Li, Chenxu Wang +2
In this work, we present CollabVLA, a self-reflective vision-language-action framework that transforms a standard visuomotor policy into a collaborative assistant. CollabVLA tackle…
AssistantX: An LLM-Powered Proactive Assistant in Collaborative Human-Populated Environment
Nan Sun, Bo Mao, Yongchang Li +2
Current service robots suffer from limited natural language communication abilities, heavy reliance on predefined commands, ongoing human intervention, and, most notably, a lack of…