Yao Mu

M2Tok: Multi-head Multi-codebook Discrete Action Tokenization for Vision-Language-Action Models

Recent advancements have successfully adapted autoregressive language models to process multimodal signals, such as images and actions. Since raw action signals are continuous, effective tokenization is essential to map high-dimensional inputs into compact discrete tokens for autoregressive processing. However, existin...

H2R-Bench: Benchmarking Human-to-Robot Manipulation Video Generation in World Models

Large-scale manipulation data is essential for robot learning, yet collecting robot demonstrations remains expensive and difficult to scale. Meanwhile, abundant egocentric human manipulation videos provide rich behavioral experiences, but transferring them across embodiments remains challenging due to differences betwe...

MoEActok: A MoE-based Action Tokenizer for Vision-Language-Action Models