Sotabase

Career

· Research Intern, Allen Institute for Artificial Intelligence (AI2)2025–
· Research Intern, Allen Institute for AI (AI2)2024–
· Research Consultant, Snorkel AI2024–2025
· Research Intern, Microsoft2023–2023
· Course Assistant, Stanford University2023–2023
· PhD in Computer Science, Stanford University2019–
· PhD Student in Computer Science (Hazy Research Lab), Stanford University2019–
· Quantitative Trading Intern, IMC Trading2018–2018
· Intern, Google2017–2017
· Engineering Practicum Intern, Google2016–2016
· Grader for Computer Science Department, Princeton University2016–2019
· B.S. in Operations Research and Financial Engineering, Princeton University2015–2019
· BS in Operations Research and Financial Engineering, Princeton University2015–2019
· Research Assistant, Princeton University2015–

Publications (33)

Ask Me Anything: A simple strategy for prompting language models
International Conference on Learning Representations · 2022
256
cited
Fast and Three-rious: Speeding Up Weak Supervision with Triplet Methods
International Conference on Machine Learning · 2020
126
cited
Skill-it! A Data-Driven Skills Framework for Understanding and Training Language Models
Neural Information Processing Systems · 2023
96
cited
Mandoline: Model Evaluation under Distribution Shift
International Conference on Machine Learning · 2021
81
cited
Perfectly Balanced: Improving Transfer and Robustness of Supervised Contrastive Learning
International Conference on Machine Learning · 2022
58
cited
Smoothie: Label Free Language Model Routing
Neural Information Processing Systems · 2024
23
cited
Shoring Up the Foundations: Fusing Model Embeddings and Weak Supervision
Conference on Uncertainty in Artificial Intelligence · 2022
20
cited
Aioli: A Unified Optimization Framework for Language Model Data Mixing
International Conference on Learning Representations · 2024
16
cited
Effect of rotational grazing on plant and animal production.
Mathematical biosciences and engineering : MBE · 2017
13
cited
Reducing Reliance on Spurious Features in Medical Image Classification with Spatial Specificity
Machine Learning in Health Care · 2022
13
cited
TABi: Type-Aware Bi-Encoders for Open-Domain Entity Retrieval
Findings · 2022
12
cited
Comparing the Value of Labeled and Unlabeled Data in Method-of-Moments Latent Variable Estimation
International Conference on Artificial Intelligence and Statistics · 2021
10
cited
The Details Matter: Preventing Class Collapse in Supervised Contrastive Learning
AAAI Workshop on Artificial Intelligence with Biased or Scarce Data (AIBSD) · 2022
10
cited
Train and You'll Miss It: Interactive Model Iteration with Weak Supervision and Pre-Trained Embeddings
arXiv.org · 2020
10
cited
A case for reframing automated medical image classification as segmentation
Neural Information Processing Systems · 2023
9
cited
Network disruption: maximizing disagreement and polarization in social networks
arXiv.org · 2020
9
cited
Shrinking the Generation-Verification Gap with Weak Verifiers
arXiv.org · 2025
9
cited
Resonant anomaly detection with multiple reference datasets
Journal of High Energy Physics · 2022
8
cited
Cookbook: A framework for improving LLM generative abilities via programmatic data generating templates
arXiv.org · 2024
4
cited
Embroid: Unsupervised Prediction Smoothing Can Improve Few-Shot Classification
Neural Information Processing Systems · 2023
4
cited
Sotabase
Mayee F. Chen | Researcher Profile | Sotabase | Sotabase