2 papers
cs.RO2026
WALA Learning Executable Latent Actions from Action-Labeled Demonstrations and Action-Free Videos
Jiahao Liu, Zhongpu Xia, Shuai Tian +13
Generalizable robot policies typically rely on action-labeled robot demonstrations, which are expensive to collect and difficult to scale. In contrast, large-scale human and robot…
cs.RO2026
WoVR: World Models as Reliable Simulators for Post-Training VLA Policies with RL
Zhennan Jiang, Shangqing Zhou, Yutong Jiang +11
Reinforcement learning (RL) promises to unlock capabilities beyond imitation learning for Vision--Language--Action (VLA) models, but its requirement for massive real-world interact…