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Harsha Nori

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Data Science with LLMs and Interpretable Models

Feb 22, 2024
Sebastian Bordt, Ben Lengerich, Harsha Nori, Rich Caruana

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Can Generalist Foundation Models Outcompete Special-Purpose Tuning? Case Study in Medicine

Nov 28, 2023
Harsha Nori, Yin Tat Lee, Sheng Zhang, Dean Carignan, Richard Edgar, Nicolo Fusi, Nicholas King, Jonathan Larson, Yuanzhi Li, Weishung Liu, Renqian Luo, Scott Mayer McKinney, Robert Osazuwa Ness, Hoifung Poon, Tao Qin, Naoto Usuyama, Chris White, Eric Horvitz

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Interpretable Predictive Models to Understand Risk Factors for Maternal and Fetal Outcomes

Oct 16, 2023
Tomas M. Bosschieter, Zifei Xu, Hui Lan, Benjamin J. Lengerich, Harsha Nori, Ian Painter, Vivienne Souter, Rich Caruana

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LLMs Understand Glass-Box Models, Discover Surprises, and Suggest Repairs

Aug 07, 2023
Benjamin J. Lengerich, Sebastian Bordt, Harsha Nori, Mark E. Nunnally, Yin Aphinyanaphongs, Manolis Kellis, Rich Caruana

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Differentially Private Synthetic Data via Foundation Model APIs 1: Images

May 24, 2023
Zinan Lin, Sivakanth Gopi, Janardhan Kulkarni, Harsha Nori, Sergey Yekhanin

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Sparks of Artificial General Intelligence: Early experiments with GPT-4

Mar 27, 2023
Sébastien Bubeck, Varun Chandrasekaran, Ronen Eldan, Johannes Gehrke, Eric Horvitz, Ece Kamar, Peter Lee, Yin Tat Lee, Yuanzhi Li, Scott Lundberg, Harsha Nori, Hamid Palangi, Marco Tulio Ribeiro, Yi Zhang

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Capabilities of GPT-4 on Medical Challenge Problems

Mar 20, 2023
Harsha Nori, Nicholas King, Scott Mayer McKinney, Dean Carignan, Eric Horvitz

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Using Interpretable Machine Learning to Predict Maternal and Fetal Outcomes

Jul 12, 2022
Tomas M. Bosschieter, Zifei Xu, Hui Lan, Benjamin J. Lengerich, Harsha Nori, Kristin Sitcov, Vivienne Souter, Rich Caruana

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