// PERSON
Nie Lin
AT UNIVERSITY OF TOKYOMENTIONS 4LAST SEEN AUGUST 4, 2026
// RECENT MENTIONS
// SIGNALS
4 SIGNALS
01
product·arXiv Physical AI·AUGUST 4, 2026
“SiMDex uses only ~1.49M mined samples (<5% of the pool) yet improves the overall success rate from 47.7% to 61.1%”
Source→02
mention·arXiv Physical AI·AUGUST 4, 2026
“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.”
Source→03
product·arXiv Physical AI·AUGUST 4, 2026
“His lab has produced multiple related works including SiMHand (hand pose pre-training)”
Source→04
hire·arXiv Physical AI·AUGUST 4, 2026
“First author who developed the SiMDex framework. Also authored SiMHand (ICLR 2025), a similar mining approach for 3D hand pose pre-training.”
Source→AI-extracted from podcast / newsletter / paper summaries. May contain errors.