Vincent Sunn Chen

writing

Benchmarks should shape the frontier, not just measure it · Apr 2026
Closing the Evaluation Gap in Agentic AI · Feb 2026
Design Principles for Iteratively Building AI Applications · Nov 2021
Learning Math for Machine Learning · Aug 2018
Building for the Blockchain (with Ramon Recuero) · Jan 2018
How to Get into VR · May 2017
How To Get Into Natural Language Processing · Jan 2017

publications

Slice-based Learning: A Programming Model for Residual Learning in Critical Data Slices

Vincent S Chen, Zhenzhen Weng, Alexander Ratner, Christopher Ré

NeurIPS 2019 · blog · slides · paper · code

Scene Graph Prediction with Limited Labels

Vincent S Chen, Paroma Varma, Ranjay Krishna, Michael Bernstein, Christopher Ré, Li Fei-Fei

ICCV 2019 · paper · code · poster

Powerful Abstractions for Programming Your Training Data

Sen Wu, Vincent S. Chen, Braden Hancock, Alex Ratner, Chris Ré, and other members of Hazy Lab

SuperGLUE Benchmark · blog · code

Massive Multi-Task Learning: Bringing More Supervision to Bear

Braden Hancock, Clara McCreery, Ines Chami, Vincent S. Chen, Sen Wu, Jared Dunnmon, Paroma Varma, Max Lam, Chris Ré

GLUE Benchmark · blog

Weakly supervised classification of rare aortic valve malformations using unlabeled cardiac MRI sequences

Jason A Fries, Paroma Varma, Vincent S Chen, Ke Xiao, Heliodoro Tejeda, Priyanka Saha, Jared Dunnmon, Henry Chubb, Shiraz Maskatia, Madalina Fiterau, Scott Delp, Euan Ashley, Christopher Ré, James Priest

Nature Communications 2019 · paper · code

Automated Training Set Generation for Aortic Valve Classification

Vincent Chen, Paroma Varma, Madalina Fiterau, James Priest, Christopher Ré

NeurIPS 2017, ML4H Workshop · poster

teaching

CS231N: Convolutional Neural Networks for Visual Recognition

Teaching Assistant, Spring 2018

Hosted office hours, advised student projects, and led discussion sections on backpropagation and weak supervision.