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Stefan Hegselmann

2 accepted papers

2023

TabLLM: Few-shot Classification of Tabular Data with Large Language Models

AISTATS 2023poster

We study the application of large language models to zero-shot and few-shot classification of tabular data. We prompt the large language model with a serialization of the tabular data to a natural-language string, together with a short description of the classification problem. In the few-shot setti…

2022

Large language models are few-shot clinical information extractors

EMNLP 2022main

A long-running goal of the clinical NLP community is the extraction of important variables trapped in clinical notes. However, roadblocks have included dataset shift from the general domain and a lack of public clinical corpora and annotations. In this work, we show that large language models, such…

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