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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Abstract
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 |
| URI: | http://eprints.uet.vnu.edu.vn/eprints/id/eprint/2912 |
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