Shuai Yang

Human video demonstrations can transform robot learning, enabling zero-shot generalization to unseen tasks with remarkable success rates.

ReWorld achieves unprecedented control fidelity and video generation quality by elegantly separating short-term control from long-term memory, outperforming existing models in interactive environments.

LingBot-VA 2.0 achieves few-shot generalization in complex robot manipulation tasks, outperforming traditional video generative models.

Semantic visual-action tokenization in RepWAM significantly enhances robotic manipulation performance, outperforming traditional reconstruction-based approaches.