Sotabase

Career

· Intern, FAIR2024–
· PhD Student, MIT2020–
· Graduate Student, MIT2017–2018
· AI Resident, Microsoft Research AI
· M.Eng., MIT
· Undergraduate, MIT

Publications (42)

Large language models are few-shot clinical information extractors
Conference on Empirical Methods in Natural Language Processing · 2022
436
cited
TabLLM: Few-shot Classification of Tabular Data with Large Language Models
International Conference on Artificial Intelligence and Statistics · 2022
334
cited
Understanding the Role of Momentum in Stochastic Gradient Methods
Neural Information Processing Systems · 2019
106
cited
Who Should Predict? Exact Algorithms For Learning to Defer to Humans
International Conference on Artificial Intelligence and Statistics · 2023
71
cited
Large Language Models are Zero-Shot Clinical Information Extractors
arXiv.org · 2022
64
cited
Learning to Decode Collaboratively with Multiple Language Models
Annual Meeting of the Association for Computational Linguistics · 2024
56
cited
Co-training Improves Prompt-based Learning for Large Language Models
International Conference on Machine Learning · 2022
47
cited
Theoretical Analysis of Weak-to-Strong Generalization
Neural Information Processing Systems · 2024
39
cited
Using Statistics to Automate Stochastic Optimization
Neural Information Processing Systems · 2019
24
cited
Training Subset Selection for Weak Supervision
Neural Information Processing Systems · 2022
23
cited
When One LLM Drools, Multi-LLM Collaboration Rules
arXiv.org · 2025
21
cited
Self-supervised self-supervision by combining deep learning and probabilistic logic
AAAI Conference on Artificial Intelligence · 2020
13
cited
Statistical Adaptive Stochastic Gradient Methods
arXiv.org · 2020
12
cited
Leveraging Time Irreversibility with Order-Contrastive Pre-training
International Conference on Artificial Intelligence and Statistics · 2021
10
cited
Optimality of Approximate Inference Algorithms on Stable Instances
International Conference on Artificial Intelligence and Statistics · 2017
8
cited
Block Stability for MAP Inference
International Conference on Artificial Intelligence and Statistics · 2018
6
cited
Beyond Perturbation Stability: LP Recovery Guarantees for MAP Inference on Noisy Stable Instances
International Conference on Artificial Intelligence and Statistics · 2021
3
cited
Combining Probabilistic Logic and Deep Learning for Self-Supervised Learning
Neuro-Symbolic Artificial Intelligence · 2021
2
cited
Alpha-expansion is Exact on Stable Instances
arXiv.org · 2017
1
cited
Graph Cuts Always Find a Global Optimum for Potts Models (With a Catch)
International Conference on Machine Learning · 2020
1
cited
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Hunter Lang | Researcher Profile | Sotabase | Sotabase