%0 Conference Paper
%A Le, Hoang Quynh
%A Vuong, Thi Hai Yen
%A Nguyen, Minh Trang
%B BioNLP-NAACL 2021
%D 2021
%F SisLab:4492
%T UETfishes at MEDIQA 2021: Standing-on-the-Shoulders-of-Giants Model for Abstractive Multi-answer Summarization
%U https://eprints.uet.vnu.edu.vn/eprints/id/eprint/4492/
%X This paper describes a system developed to  summarize multiple answers challenge in the  MEDIQA 2021 shared task collocated with  the BioNLP 2021 Workshop. We present  an abstractive summarization model based  on BART, a denoising auto-encoder for pre�training sequence-to-sequence models. As focusing on the summarization of answers to consumer health questions, we propose a query-driven filtering phase to choose useful information from the input document automat�ically. Our approach achieves potential results, rank no.2 (evaluated on extractive references) and no.3 (evaluated on abstractive references)  in the final evaluation.