3 citations · 5 across the 10 of their papers we have counts for
3 papers · 1 filter
Context-Adaptive Inference: A Unified Statistical and Foundation-Model View
Yue Yao, Caleb N. Ellington, Jingyun Jia +9
Modern predictive systems are expected to adapt their behavior to the specific situation they are facing. A clinical model should not treat every patient the same; a retrieval-augm…
Contextualized Machine Learning
Benjamin Lengerich, Caleb N. Ellington, Andrea Rubbi +2
We examine Contextualized Machine Learning (ML), a paradigm for learning heterogeneous and context-dependent effects. Contextualized ML estimates heterogeneous functions by applyin…
LLMs Understand Glass-Box Models, Discover Surprises, and Suggest Repairs
Benjamin J. Lengerich, Sebastian Bordt, Harsha Nori +4
We show that large language models (LLMs) are remarkably good at working with interpretable models that decompose complex outcomes into univariate graph-represented components. By…