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RNN on Machine Reading Comprehension Bi-Directional Attention Flow model

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.

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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.

Item Type: Technical Report (Technical Report)
Uncontrolled Keywords: RNN, Natural Language Processing
Subjects: Electronics and Communications
Divisions: Faculty of Electronics and Telecommunications (FET)
Depositing User: Hong Thinh Nguyen
Date Deposited: 12 Jan 2018 02:00
Last Modified: 12 Jan 2018 02:00

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