Human Demonstrations Need a Relevance Filter Before VLA Post-Training
TL;DR for operators A robotics team may have a small, expensive set of demonstrations from its target robot and a much larger pool of cheaper human demonstrations of apparently similar tasks. The tempting move is to combine them. The paper’s randomized simulation results show why that decision needs more control: robot-only training averages 0.34 task success, while randomly mixed human data falls to 0.32. Selecting human demonstrations by relevance raises the average to 0.40, and adding sample-specific weighting raises it further to 0.42. ...