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Found 3 papers, 1 papers with code
Impact of Large Language Model Assistance on Patients Reading Clinical Notes: A Mixed-Methods Study
Augmentations were evaluated for errors by clinicians, and we found misleading errors occur, with errors more common in real donated notes than synthetic notes, illustrating the importance of carefully written clinical notes.
TabLLM: Few-shot Classification of Tabular Data with Large Language Models
We study the application of large language models to zero-shot and few-shot classification of tabular data.
Examination and Extension of Strategies for Improving Personalized Language Modeling via Interpolation
In this paper, we detail novel strategies for interpolating personalized language models and methods to handle out-of-vocabulary (OOV) tokens to improve personalized language models.
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