June 7, 2024, 4:51 a.m. | Anand Subramanian, Viktor Schlegel, Abhinav Ramesh Kashyap, Thanh-Tung Nguyen, Vijay Prakash Dwivedi, Stefan Winkler

cs.CL updates on arXiv.org arxiv.org

arXiv:2406.03699v1 Announce Type: new
Abstract: There is vivid research on adapting Large Language Models (LLMs) to perform a variety of tasks in high-stakes domains such as healthcare. Despite their popularity, there is a lack of understanding of the extent and contributing factors that allow LLMs to recall relevant knowledge and combine it with presented information in the clinical and biomedical domain: a fundamental pre-requisite for success on down-stream tasks. Addressing this gap, we use Multiple Choice and Abstractive Question Answering …

abstract arxiv benchmark clinical cs.cl domains healthcare knowledge language language models large language large language models llms question question answering reading recall research tasks type understanding via

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