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        <title>Large Language Models as Instructors: A Study on Multilingual Clinical Entity Extraction</title>
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            <namePart type="family">Demner-fushman</namePart>
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    <abstract>In clinical and other specialized domains, data are scarce due to their confidential nature. This lack of data is a major problem when fine-tuning language models. Nevertheless, very large language models (LLMs) are promising for the medical domain but cannot be used directly in healthcare facilities due to data confidentiality issues. We explore an approach of annotating training data with LLMs to train smaller models more adapted to our problem. We show that this method yields promising results for information extraction tasks.</abstract>
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%0 Conference Proceedings
%T Large Language Models as Instructors: A Study on Multilingual Clinical Entity Extraction
%A Meoni, Simon
%A De la Clergerie, Eric
%A Ryffel, Theo
%Y Demner-fushman, Dina
%Y Ananiadou, Sophia
%Y Cohen, Kevin
%S The 22nd Workshop on Biomedical Natural Language Processing and BioNLP Shared Tasks
%D 2023
%8 July
%I Association for Computational Linguistics
%C Toronto, Canada
%F meoni-etal-2023-large
%X In clinical and other specialized domains, data are scarce due to their confidential nature. This lack of data is a major problem when fine-tuning language models. Nevertheless, very large language models (LLMs) are promising for the medical domain but cannot be used directly in healthcare facilities due to data confidentiality issues. We explore an approach of annotating training data with LLMs to train smaller models more adapted to our problem. We show that this method yields promising results for information extraction tasks.
%R 10.18653/v1/2023.bionlp-1.15
%U https://aclanthology.org/2023.bionlp-1.15
%U https://doi.org/10.18653/v1/2023.bionlp-1.15
%P 178-190

Markdown (Informal)

[Large Language Models as Instructors: A Study on Multilingual Clinical Entity Extraction](https://aclanthology.org/2023.bionlp-1.15) (Meoni et al., BioNLP 2023)

• Large Language Models as Instructors: A Study on Multilingual Clinical Entity Extraction (Meoni et al., BioNLP 2023)

ACL

• Simon Meoni, Eric De la Clergerie, and Theo Ryffel. 2023. Large Language Models as Instructors: A Study on Multilingual Clinical Entity Extraction. In The 22nd Workshop on Biomedical Natural Language Processing and BioNLP Shared Tasks, pages 178–190, Toronto, Canada. Association for Computational Linguistics.