Sotabase

Career

· PhD in Computer Science, Stanford University2021–
· JD Candidate, Stanford Law School2020–2026
· Graduate Student Fellow at RegLab, Stanford University2019–
· MS in Machine Learning, Carnegie Mellon University2018–2019
· Policy Intern, Federal Communications Commission2017–
· Intern, Laserlike2017–
· Intern, Google2016–
· Research Assistant, Institute for Quantitative Social Science, Harvard2015–
· BS with Honors in Computer Science, Stanford University2014–2018

Publications (66)

On the Opportunities and Risks of Foundation Models
arXiv.org · 2021
5,795
cited
Holistic Evaluation of Language Models
Trans. Mach. Learn. Res. · 2023
1,324
cited
LegalBench: A Collaboratively Built Benchmark for Measuring Legal Reasoning in Large Language Models
Social Science Research Network · 2023
314
cited
When does pretraining help?: assessing self-supervised learning for law and the CaseHOLD dataset of 53,000+ legal holdings
International Conference on Artificial Intelligence and Law · 2021
299
cited
Ask Me Anything: A simple strategy for prompting language models
International Conference on Learning Representations · 2022
256
cited
One-Shot Federated Learning
arXiv.org · 2019
244
cited
Pile of Law: Learning Responsible Data Filtering from the Law and a 256GB Open-Source Legal Dataset
Neural Information Processing Systems · 2022
129
cited
When Benchmarks are Targets: Revealing the Sensitivity of Large Language Model Leaderboards
Annual Meeting of the Association for Computational Linguistics · 2024
119
cited
Leveraging Administrative Data for Bias Audits: Assessing Disparate Coverage with Mobility Data for COVID-19 Policy
Conference on Fairness, Accountability and Transparency · 2020
77
cited
Machine Learning for AC Optimal Power Flow
arXiv.org · 2019
75
cited
Understanding Liability Risk from Using Health Care Artificial Intelligence Tools.
New England Journal of Medicine · 2024
69
cited
ChatGPT and Physicians' Malpractice Risk.
JAMA Health Forum · 2023
61
cited
Open Problems in Technical AI Governance
arXiv.org · 2024
55
cited
Bootleg: Chasing the Tail with Self-Supervised Named Entity Disambiguation
Conference on Innovative Data Systems Research · 2020
49
cited
Archon: An Architecture Search Framework for Inference-Time Techniques
International Conference on Machine Learning · 2024
42
cited
Benchmarking and Building Long-Context Retrieval Models with LoCo and M2-BERT
International Conference on Machine Learning · 2024
23
cited
LegalBench: Prototyping a Collaborative Benchmark for Legal Reasoning
arXiv.org · 2022
23
cited
Smoothie: Label Free Language Model Routing
Neural Information Processing Systems · 2024
23
cited
Cartridges: Lightweight and general-purpose long context representations via self-study
arXiv.org · 2025
18
cited
Don't Use a Cannon to Kill a Fly: An Efficient Cascading Pipeline for Long Documents
International Conference on Artificial Intelligence and Law · 2023
9
cited
Sotabase
Neel Guha | Researcher Profile | Sotabase | Sotabase