NCUEE-NLP at MEDIQA 2021: Health Question Summarization Using PEGASUS Transformers

Lung-Hao Lee, Po-Han Chen, Yu-Xiang Zeng, Po-Lei Lee, Kuo-Kai Shyu


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.
Anthology ID:
2021.bionlp-1.30
Volume:
Proceedings of the 20th Workshop on Biomedical Language Processing
Month:
June
Year:
2021
Address:
Online
Venues:
BioNLP | NAACL
SIG:
SIGBIOMED
Publisher:
Association for Computational Linguistics
Note:
Pages:
268–272
Language:
URL:
https://aclanthology.org/2021.bionlp-1.30
DOI:
10.18653/v1/2021.bionlp-1.30
Bibkey:
Cite (ACL):
Lung-Hao Lee, Po-Han Chen, Yu-Xiang Zeng, Po-Lei Lee, and Kuo-Kai Shyu. 2021. NCUEE-NLP at MEDIQA 2021: Health Question Summarization Using PEGASUS Transformers. In Proceedings of the 20th Workshop on Biomedical Language Processing, pages 268–272, Online. Association for Computational Linguistics.
Cite (Informal):
NCUEE-NLP at MEDIQA 2021: Health Question Summarization Using PEGASUS Transformers (Lee et al., BioNLP 2021)
Copy Citation:
PDF:
https://aclanthology.org/2021.bionlp-1.30.pdf
Data
Medical Question Pairs