Zero-Shot Generalization

A policy's ability to succeed on a task or with an object that was never seen during training, without any adaptation or fine-tuning. Zero-shot generalization is the ultimate goal of general-purpose robot learning. VLA models pre-trained on internet-scale data and diverse robot datasets demonstrate increasing zero-shot capabilities, though reliability remains a challenge.