relation: https://eprints.uet.vnu.edu.vn/eprints/id/eprint/4492/
title: UETfishes at MEDIQA 2021: Standing-on-the-Shoulders-of-Giants Model for Abstractive Multi-answer Summarization
creator: Le, Hoang Quynh
creator: Vuong, Thi Hai Yen
creator: Nguyen, Minh Trang
subject: Electronics and Computer Engineering
description: 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.
date: 2021
type: Conference or Workshop Item
type: PeerReviewed
format: application/pdf
language: en
identifier: https://eprints.uet.vnu.edu.vn/eprints/id/eprint/4492/1/UETfishes_at_MEDIQA_2021__Standing_on_the_Shoulders_of_Giants_Model_for_Abstractive_Multi_answer_Summarization.pdf
identifier:   Le, Hoang Quynh and Vuong, Thi Hai Yen and Nguyen, Minh Trang  (2021) UETfishes at MEDIQA 2021: Standing-on-the-Shoulders-of-Giants Model for Abstractive Multi-answer Summarization.  In: BioNLP-NAACL 2021.