Rationalism in the face of GPT hypes: Benchmarking the output of large language models against human expert-curated biomedical knowledge graphs

Author:

Babaiha Negin SadatORCID,Rao Sathvik Guru,Klein Jürgen,Schultz Bruce,Jacobs Marc,Hofmann-Apitius MartinORCID

Funder

Stiftung für das Bonn-Aachen International Center for Information Technology-B-IT

Publisher

Elsevier BV

Subject

General Medicine

Reference39 articles.

1. T. Kojima, S. S. Gu, M. Reid, Y. Matsuo, and Y. Iwasawa, “Large Language Models are Zero-Shot Reasoners”.

2. ChatGPT: A comprehensive review on background, applications, key challenges, bias, ethics, limitations and future scope;Ray;Internet of Things and Cyber-Physical Systems,2023

3. “Recent Advances in Natural Language Processing via Large Pre-trained Language Models: A Survey | ACM Computing Surveys.” Accessed: Nov. 22, 2023. [Online]. Available: https://dl.acm.org/doi/full/10.1145/3605943?casa_token=ONsF3vqeb4cAAAAA%3AAyPn06seNfuPdWwhb8uUIzfo0Yt3zlqL0BZFvMgqzy97vm8BN2F5m-k-Z4_QdwiKkRB6OLICRd5sNg

4. A Survey on In-context Learning;Dong,2023

5. Prompt Engineering for Healthcare: Methodologies and Applications;Wang,2023

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