%A Hoang Quynh Le
%A Thi Hai Yen Vuong
%A Minh Trang Nguyen
%T UETfishes at MEDIQA 2021: Standing-on-the-Shoulders-of-Giants Model for Abstractive Multi-answer Summarization
%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.
%D 2021
%L SisLab4492