April 30, 2024, 4:50 a.m. | Yunyi Liu, Zhanyu Wang, Yingshu Li, Xinyu Liang, Lingqiao Liu, Lei Wang, Luping Zhou

cs.CL updates on arXiv.org arxiv.org

arXiv:2404.17778v1 Announce Type: new
Abstract: In recent years, automated radiology report generation has experienced significant growth. This paper introduces MRScore, an automatic evaluation metric tailored for radiology report generation by leveraging Large Language Models (LLMs). Conventional NLG (natural language generation) metrics like BLEU are inadequate for accurately assessing the generated radiology reports, as systematically demonstrated by our observations within this paper. To address this challenge, we collaborated with radiologists to develop a framework that guides LLMs for radiology report evaluation, …

abstract arxiv automated bleu cs.ai cs.cl evaluation generated growth language language generation language models large language large language models llm llms metrics natural natural language natural language generation nlg paper radiology report reward system type

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