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Department of Mathematics, School of Mathematics, Purdue University, Georgia Institute of Technology
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Transformers can be explicitly designed to perform nonlinear regression in-context by leveraging attention as a featurizer, offering a theoretical understanding of how these models learn complex relationships from prompts.
