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cs.RO2025
It Takes Two: Learning Interactive Whole-Body Control Between Humanoid Robots
Zuhong Liu, Junhao Ge, Minhao Xiong +4
The true promise of humanoid robotics lies beyond single-agent autonomy: two or more humanoids must engage in physically grounded, socially meaningful whole-body interactions that…
cs.RO2025
Unraveling the Effects of Synthetic Data on End-to-End Autonomous Driving
Junhao Ge, Zuhong Liu, Longteng Fan +5
End-to-end (E2E) autonomous driving (AD) models require diverse, high-quality data to perform well across various driving scenarios. However, collecting large-scale real-world data…