Evaluation of Large Language Models for Summarization Tasks in the Medical Domain: A Narrative Review
<|reference_start|>Evaluation of Large Language Models for Summarization Tasks in the Medical Domain: A Narrative Review: Large Language Models have advanced clinical Natural Language Generation, creating opportunities to manage the volume of medical text. However, the high-stakes nature of medicine requires reliable evaluation, which remains a challenge. In this narrative review, we assess the current evaluation state for clinical summarization tasks and propose future directions to address the resource constraints of expert human evaluation.<|reference_end|>
@article{croxford2024evaluation,
    title={Evaluation of Large Language Models for Summarization Tasks in the
  Medical Domain: A Narrative Review},
    author={Emma Croxford, Yanjun Gao, Nicholas Pellegrino, Karen K. Wong, Graham
  Wills, Elliot First, Frank J. Liao, Cherodeep Goswami, Brian Patterson, Majid
  Afshar},
    journal={arXiv preprint arXiv:2409.18170},
    year={2024},
    archivePrefix={arXiv},
    eprint={2409.18170},
    primaryClass={cs.CL cs.AI}
}