Yoichi Sato

“SiMDex uses only ~1.49M mined samples (<5% of the pool) yet improves the overall success rate from 47.7% to 61.1%”

“The paper's central finding is that *which* human video data you feed a VLA matters more than *how much*. This directly challenges the prevailing 'just scale data' philosophy in robotics.”

“His lab has produced multiple related works including SiMHand (hand pose pre-training)”

“Leading computer vision researcher, particularly in egocentric video understanding.”