Evaluating Large Language Models on Medical Evidence Summarization

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Recent advances in large language models (LLMs) have demonstrated remarkable successes in zero- and few-shot performance on various downstream tasks, paving the way for applications in high-stakes domains. In this study, we systematically examine the capabilities and limitations of LLMs, specificall...

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Detalles Bibliográficos
Autores principales: Tang, Liyan, Sun, Zhaoyi, Idnay, Betina, Nestor, Jordan G, Soroush, Ali, Elias, Pierre A., Xu, Ziyang, Ding, Ying, Durrett, Greg, Rousseau, Justin, Weng, Chunhua, Peng, Yifan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Cold Spring Harbor Laboratory 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10168498/
https://www.ncbi.nlm.nih.gov/pubmed/37162998
http://dx.doi.org/10.1101/2023.04.22.23288967

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10168498/
https://www.ncbi.nlm.nih.gov/pubmed/37162998
http://dx.doi.org/10.1101/2023.04.22.23288967

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