Sotabase

Career

· Associate Professor (By courtesy), Statistics, Stanford University2018–
· Associate Professor, Stanford University2012–
· Postdoctoral Researcher, Google2011–2012
· Doctor of Philosophy (Ph.D.), UC Berkeley2005–2011
· Master of Engineering (MEng), MIT2004–2005
· Bachelor of Science (B.S.), MIT2000–2004
· Senior Fellow, Institute for Human-Centered Artificial Intelligence (HAI), Stanford University

Publications (571)

SQuAD: 100,000+ Questions for Machine Comprehension of Text
Conference on Empirical Methods in Natural Language Processing · 2016
9,019
cited
On the Opportunities and Risks of Foundation Models
arXiv.org · 2021
5,795
cited
Prefix-Tuning: Optimizing Continuous Prompts for Generation
Annual Meeting of the Association for Computational Linguistics · 2021
5,318
cited
Understanding Black-box Predictions via Influence Functions
International Conference on Machine Learning · 2017
3,338
cited
Generative Agents: Interactive Simulacra of Human Behavior
ACM Symposium on User Interface Software and Technology · 2023
3,168
cited
Know What You Don’t Know: Unanswerable Questions for SQuAD
Annual Meeting of the Association for Computational Linguistics · 2018
3,153
cited
Lost in the Middle: How Language Models Use Long Contexts
Transactions of the Association for Computational Linguistics · 2023
2,811
cited
Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models
arXiv.org · 2022
2,201
cited
Semantic Parsing on Freebase from Question-Answer Pairs
Conference on Empirical Methods in Natural Language Processing · 2013
2,146
cited
Adversarial Examples for Evaluating Reading Comprehension Systems
Conference on Empirical Methods in Natural Language Processing · 2017
1,678
cited
Strategies for Pre-training Graph Neural Networks
International Conference on Learning Representations · 2019
1,675
cited
WILDS: A Benchmark of in-the-Wild Distribution Shifts
International Conference on Machine Learning · 2020
1,674
cited
OpenVLA: An Open-Source Vision-Language-Action Model
Conference on Robot Learning · 2024
1,478
cited
Distributionally Robust Neural Networks for Group Shifts: On the Importance of Regularization for Worst-Case Generalization
arXiv.org · 2019
1,471
cited
Holistic Evaluation of Language Models
Trans. Mach. Learn. Res. · 2023
1,324
cited
Diffusion-LM Improves Controllable Text Generation
Neural Information Processing Systems · 2022
1,141
cited
Concept Bottleneck Models
International Conference on Machine Learning · 2020
1,089
cited
Certified Defenses against Adversarial Examples
International Conference on Learning Representations · 2018
992
cited
s1: Simple test-time scaling
Conference on Empirical Methods in Natural Language Processing · 2025
967
cited
An Explanation of In-context Learning as Implicit Bayesian Inference
International Conference on Learning Representations · 2021
950
cited
Sotabase