3 papers
cs.RO2026
FluxVLA Engine: A One-Stop VLA Engineering Platform for Embodied Intelligence
Yinhao Li, Weixin Mao, Zihan Lan +22
Vision-language-action (VLA) models, world-action models (WAMs), and offline reinforcement learning methods are rapidly expanding the design space of embodied policies, yet turning…
cs.RO2026
ARM: Advantage Reward Modeling for Long-Horizon Manipulation
Yiming Mao, Zixi Yu, Weixin Mao +5
Long-horizon robotic manipulation remains challenging for reinforcement learning (RL) because sparse rewards provide limited guidance for credit assignment. Practical policy improv…
cs.RO2025
OmniD: Generalizable Robot Manipulation Policy via Image-Based BEV Representation
Jilei Mao, Jiarui Guan, Yingjuan Tang +7
The visuomotor policy can easily overfit to its training datasets, such as fixed camera positions and backgrounds. This overfitting makes the policy perform well in the in-distribu…