@inproceedings{5592109f57ee4e3396a1fd9e2837c2e1,
title = "NCUEE-NLP at MEDIQA 2021: Health Question Summarization Using PEGASUS Transformers",
abstract = "This study describes the model design of the NCUEE-NLP system for the MEDIQA challenge at the BioNLP 2021 workshop. We use the PEGASUS transformers and fine-tune the downstream summarization task using our collected and processed datasets. A total of 22 teams participated in the consumer health question summarization task of MEDIQA 2021. Each participating team was allowed to submit a maximum of ten runs. Our best submission, achieving a ROUGE2-F1 score of 0.1597, ranked third among all 128 submissions.",
author = "Lee, {Lung Hao} and Chen, {Po Han} and Zeng, {Yu Xiang} and Lee, {Po Lei} and Shyu, {Kuo Kai}",
note = "Publisher Copyright: {\textcopyright} 2021 Association for Computational Linguistics; 20th Workshop on Biomedical Language Processing, BioNLP 2021 ; Conference date: 11-06-2021",
year = "2021",
doi = "10.18653/v1/2021.bionlp-1.30",
language = "English",
series = "Proceedings of the 20th Workshop on Biomedical Language Processing, BioNLP 2021",
publisher = "Association for Computational Linguistics (ACL)",
pages = "268--272",
editor = "Dina Demner-Fushman and Cohen, {Kevin Bretonnel} and Sophia Ananiadou and Junichi Tsujii",
booktitle = "Proceedings of the 20th Workshop on Biomedical Language Processing, BioNLP 2021",
address = "美國",
}