Teahose.
SIGN IN
NEW HERE — WHAT TEAHOSE DOES
We read the entire AI & tech firehose — so you don't have to.
PODPodcastsAll-In, No Priors, Acquired…
NEWNewslettersStratechery, Newcomer…
PAPPapersPhysical AI research
PHProduct Huntdaily launches
VCInvestor ScoutSequoia, a16z, Benchmark…
CLAUDE DISTILLS →
7 reads, 30 sec each — free, 6 AM ET.
+ a live graph of the companies, people & themes underneath.
HOME/PEOPLE/YU SUN
// PERSON

Yu Sun

ROLE RESEARCHERMENTIONS 1LAST SEEN JULY 16, 2026
// BIO

Yu Sun is a researcher at NVIDIA and a postdoctoral researcher at Stanford University, where he is hosted by Carlos Guestrin, Tatsu Hashimoto, and Sanmi Koyejo. He completed his PhD in EECS at UC Berkeley, advised by Alexei Efros and Moritz Hardt, with a thesis on test-time training. He is best known as the originator of the test-time training paradigm, which involves training a different model on-the-fly for each test instance using self-supervision.

// RECENT MENTIONS
// SIGNALS
1 SIGNAL
01
mention·arXiv Physical AI·JULY 16, 2026

Originator of the TTT paradigm. His foundational work on fast weights updated by gradient descent at test time is the core mechanism RoboTTT builds upon

Source

AI-extracted from podcast / newsletter / paper summaries. May contain errors.

Yu Sun · Researcher — 1 mention on Teahose