relation: https://eprints.uet.vnu.edu.vn/eprints/id/eprint/2912/
title: RNN on Machine Reading Comprehension Bi-Directional Attention Flow model
creator: Nguyen, Hong-Thinh
subject: Electronics and Communications
description: Although end-to-end deep neural network have gained popularity in the last few years and have been successful in several Natural Language Processing tasks, reading comprehension remains a challenging one. In this report, we presents in details the popular Bi-Directional Attention Flow model which represents the context at different level and combined the context-to-query and query-to-context direction attention. All necessary background knowledge of general Recurrent Neural Network is also discussed.
publisher: University of Engineering and Technology
date: 2017-12-15
type: Technical Report
type: NonPeerReviewed
format: application/pdf
language: en
identifier: https://eprints.uet.vnu.edu.vn/eprints/id/eprint/2912/1/technical%20report.pdf
identifier:   Nguyen, Hong-Thinh  (2017) RNN on Machine Reading Comprehension Bi-Directional Attention Flow model.  Technical Report. University of Engineering and Technology, University of Engineering and Technology.