11 papers
GigaWorld-0: World Models as Data Engine to Empower Embodied AI
GigaWorld Team, Angen Ye, Boyuan Wang +22
World models are emerging as a foundational paradigm for scalable, data-efficient embodied AI. In this work, we present GigaWorld-0, a unified world model framework designed explic…
GigaBrain-0: A World Model-Powered Vision-Language-Action Model
GigaBrain Team, Angen Ye, Boyuan Wang +24
Training Vision-Language-Action (VLA) models for generalist robots typically requires large-scale real-world robot data, which is expensive and time-consuming to collect. The ineff…
MimicDreamer: Aligning Human and Robot Demonstrations for Scalable VLA Training
Haoyun Li, Ivan Zhang, Runqi Ouyang +12
Vision Language Action (VLA) models derive their generalization capability from diverse training data, yet collecting embodied robot interaction data remains prohibitively expensiv…
EMMA: Generalizing Real-World Robot Manipulation via Generative Visual Transfer
Zhehao Dong, Xiaofeng Wang, Zheng Zhu +12
The generalization of vision-language-action (VLA) models heavily relies on diverse training data. However, acquiring large-scale data for robot manipulation across varied object a…
ReconDreamer-RL: Enhancing Reinforcement Learning via Diffusion-based Scene Reconstruction
Chaojun Ni, Guosheng Zhao, Xiaofeng Wang +6
Reinforcement learning for training end-to-end autonomous driving models in closed-loop simulations is gaining growing attention. However, most simulation environments differ signi…
Humanoid Occupancy: Enabling A Generalized Multimodal Occupancy Perception System on Humanoid Robots
Wei Cui, Haoyu Wang, Wenkang Qin +19
Humanoid robot technology is advancing rapidly, with manufacturers introducing diverse heterogeneous visual perception modules tailored to specific scenarios. Among various percept…