7 papers
Motus2: A Self-Evolving General World Model for Dexterous Manipulation
Hongzhe Bi, Zihao Zhou, Yihang Tang +16
General embodied agents should perceive, predict, act, evaluate, and improve within a unified system. World models have shown great promise in building such agents, yet existing mo…
XPolicyLab: A Unified Standard and Open Ecosystem for Robot Policy Evaluation and Deployment
XPolicyLab Community, Tianxing Chen, Yue Chen +67
Robot policy evaluation and deployment remain fragmented by model-specific software dependencies, data representations, and runtime interfaces, so that connecting N policies to M e…
Motubrain: An Advanced World Action Model for Robot Control
Motubrain Team, Chendong Xiang, Fan Bao +17
Vision-Language-Action (VLA) models generalize semantically well but often lack fine-grained modeling of world dynamics. We present Motubrain, a unified World Action Model that joi…
HoloBrain-0 Technical Report
Xuewu Lin, Tianwei Lin, Yun Du +12
In this work, we introduce HoloBrain-0, a comprehensive Vision-Language-Action (VLA) framework that bridges the gap between foundation model research and reliable real-world robot…
Motus: A Unified Latent Action World Model
Hongzhe Bi, Hengkai Tan, Shenghao Xie +13
While a general embodied agent must function as a unified system, current methods are built on isolated models for understanding, world modeling, and control. This fragmentation pr…
H-RDT: Human Manipulation Enhanced Bimanual Robotic Manipulation
Hongzhe Bi, Lingxuan Wu, Tianwei Lin +4
Imitation learning for robotic manipulation faces a fundamental challenge: the scarcity of large-scale, high-quality robot demonstration data. Recent robotic foundation models ofte…