Houjun's Academic Home Page

Last edited: July 7, 2026

👋 Howdy, I'm Houjun Liu!

I’m a third-year coterminal MSCS and BSCS student in the Computer Science Department at Stanford University, grateful to be advised by Prof. Mykel Kochenderfer. In the course of my research, I have also had the fortunate opportunity to work with Stanford NLP under Prof. Chris Manning, CMU TalkBank under Prof. Brian MacWhinney, and Prof. Xin Liu at UC Davis Engineering. I am affiliated with the Stanford NLP Group and Stanford Intelligent Systems Lab. I’m visiting Microsoft Research Frontiers as a research intern.

Last edited: July 7, 2026

To what extend should we be making AI Safety as a public problem.

Try to find independent sources of data, with contracts for how the data must be used.

Some random Instagram influencer had more accesses than our usual methods of scientific communication.

Last edited: July 7, 2026

Last edited: July 7, 2026

Last edited: July 7, 2026

“How can we evolve the optimization algorithm itself during training?”

For \(W_{t}\) weight matrix and \(M_{t}\) update matrix, we weight the singular directions:

\begin{equation} W_{t+1} = W_{t} - \eta U^{(t)} \Sigma^{\rho^{(t)}} V^{(t)} \end{equation}

and in particular we can dial up and down your choice of \(\rho\) and do stuff. some choices of \(p\):

\(p=0\), muon OG, the idea of muon is to set all singular values to 1 so that we only prioritize direction
\(p=1\), some aggressive weight-based updates, proposed idea,
\(p < 0\), then we prioritize adjusting small directions

generally key insight: “in the beginning, we should prioritize large directions; then, we should prioritize small directions more.”