3 citations · 3 across the 11 of their papers we have counts for
4 papers · 1 filter
MV-WAM: Manifold-Aware World Action Model with Value Augmentation
Jintao Chen, Peidong Jia, Qingpo Wuwu +13
Achieving robust and generalizable manipulation across diverse environments remains a fundamental challenge in embodied robotics. Recent world action models achieve strong in-domai…
SafeDojo: Safe Reinforcement Learning for VLA via Interactive World Model
Kai Tang, Peidong Jia, Zhong Chu +15
Safe control is a prerequisite for real-world embodied intelligence, for which safe reinforcement learning has emerged as a promising paradigm. However, existing safe reinforcement…
VEGA: Visual Encoder Grounding Alignment for Spatially-Aware Vision-Language-Action Models
Hao Wang, Xiaobao Wei, Jingyang He +10
Precise spatial reasoning is fundamental to robotic manipulation, yet the visual backbones of current vision-language-action (VLA) models are predominantly pretrained on 2D image d…
RoboArmGS: High-Quality Robotic Arm Splatting via Bézier Curve Refinement
Hao Wang, Xiaobao Wei, Ying Li +6
Constructing photorealistic and controllable robotic arm digital assets from real observations is fundamental to robotic applications. Current approaches naively bind static 3D Gau…