Zhenjie Zhu

APT achieves substantial improvements in instruction generalization for VLA models by effectively decoupling language and action learning, addressing a critical data imbalance issue.

Forget painstakingly tuning force magnitudes for sim-to-real transfer of contact-rich tasks; this work shows that learning just the *direction* of contact forces unlocks surprisingly robust performance.