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.
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CITATION STYLE
Lee, L. H., Chen, P. H., Zeng, Y. X., Lee, P. L., & Shyu, K. K. (2021). NCUEE-NLP at MEDIQA 2021: Health Question Summarization Using PEGASUS Transformers. In Proceedings of the 20th Workshop on Biomedical Language Processing, BioNLP 2021 (pp. 268–272). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/2021.bionlp-1.30
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