Li, Puyin Li, Puyin

Li, Puyin

李浦银

MSc Student

Stanford University

About Me

Hello! I am a master's student in Symbolic Systems at Stanford University, advised by Thomas Icard. I also work at Stanford Translational AI (STAI) Lab as a research assistant, supervised by Ehsan Adeli. I will begin my PhD program in Computer Science at Stanford University in Fall 2026.

I am broadly interested in evaluating, improving, and interpreting foudation models' reasoning abilities as cognitive agents. This interest spans topics including causality, visual understanding and reasoning, mechanistic interpretability, formal methods, etc. My aim is to create powerful, faithful, and interpretable AI systems that can robustly interact with the noisy (physical) real-world. I believe in cross-disciplinary collaboration in AI.

Prior to Stanford, I studied logic and argumentation with Dov Gabbay and Beishui Liao (廖备水) at ZLAIRE. I am also a Morningside Culture China Scholar at Zhejiang University, which is a life-changing program initiated by a beloved professor Shengchun Zhou (周生春).

I enjoy music and tennis. I play the piano, guitar, and bass, and I’m in a band called The Wishes. I also sing alto in the Stanford Sing++ a cappella group.

Education

  • Ph.D. in Computer Science, 2026- School of Engineering, Stanford University
  • M.S. in Symbolic Systems, 2023–2026 School of Humanities and Sciences, Stanford University
  • B.A. in Philosophy (Minor in Physics), 2018–2023 Chu Kochen Honors College, Zhejiang University
  • Non-Degree Programs Visiting Student in Philosophy of Science, Mansfield College, University of Oxford, 2020-2021 Visiting Student in Management Sciences & Economy, Guanghua School of Management, Peking University, 2021-2022 Tsinghua Logic Summer School 2023; ESSLLI 2024; NASSLLI 2025.

Recent News

  • [04/2026] QuantiPhy full set is now available on HuggingFace🤗.
  • [03/2026] QuantiPhy is accepted by CVPR 2026
  • [02/2026] I am admitted to Stanford CS PhD program 🎉.

Selected Publications

QuantiPhy
QuantiPhy: A Quantitative Benchmark Evaluating Physical Reasoning Abilities of Vision-Language Models
CVPR, 2026
Li Puyin*, Tiange Xiang*, Ella Mao*, Shirley Wei, Xinye Chen, Adnan Masood, Li Fei-fei†, Ehsan Adeli†
Apple
Bucketing the Good Apples: A Method for Diagnosing and Improving Causal Abstraction
Preprint available soon
Li Puyin*, Jiyuan Tan*, Ahmad Jabbar, Thomas Icard†, Atticus Geiger†

Contact

CoDa, Stanford University