MedEval: A Multi-Level, Multi-Task, and Multi-Domain Medical Benchmark for Language Model Evaluation

Zexue He, Yu Wang, An Yan 0003, Yao Liu, Eric Y. Chang, Amilcare Gentili, Julian J. McAuley, Chun-Nan Hsu. MedEval: A Multi-Level, Multi-Task, and Multi-Domain Medical Benchmark for Language Model Evaluation. In Houda Bouamor, Juan Pino 0001, Kalika Bali, editors, Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, EMNLP 2023, Singapore, December 6-10, 2023. pages 8725-8744, Association for Computational Linguistics, 2023. [doi]

@inproceedings{HeW0LCGMH23,
  title = {MedEval: A Multi-Level, Multi-Task, and Multi-Domain Medical Benchmark for Language Model Evaluation},
  author = {Zexue He and Yu Wang and An Yan 0003 and Yao Liu and Eric Y. Chang and Amilcare Gentili and Julian J. McAuley and Chun-Nan Hsu},
  year = {2023},
  url = {https://aclanthology.org/2023.emnlp-main.540},
  researchr = {https://researchr.org/publication/HeW0LCGMH23},
  cites = {0},
  citedby = {0},
  pages = {8725-8744},
  booktitle = {Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, EMNLP 2023, Singapore, December 6-10, 2023},
  editor = {Houda Bouamor and Juan Pino 0001 and Kalika Bali},
  publisher = {Association for Computational Linguistics},
  isbn = {979-8-89176-060-8},
}