Author

Zebin Xing

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Jul 2026

WALA Learning Executable Latent Actions from Action-Labeled Demonstrations and Action-Free Videos

WALA, a framework for learning executable latent actions from both action-labeled demonstrations and action-free videos, achieves strong performance on RoboTwin, sets a new state-of-the-art result on RoboCasa, and improves both policy performance and generalization in real-world manipulation tasks.

Jia-Hao Liu, Zhongpu Xia, Shuai Tian et al. · arXiv.org · 1 citation

Preprint Aug 2026

DriveVLA-M0: Failure-Aware Memory Augmentation for Autonomous Driving

A latent memory pool is constructed that stores failure cases along with their structure scene representations and expert trajectory labels, and a dedicated Retrieve Model that decouples static road structure and dynamic agent interactions to enable structurally grounded retrieval is designed.

Zebin Xing, Yu-Peng Zheng, Qiang-Yu Chen et al. · 0 citations