@techreport{SisLab2912,
           month = {December},
          author = {Hong-Thinh Nguyen},
         address = {University of Engineering and Technology},
           title = {RNN on Machine Reading Comprehension Bi-Directional Attention Flow model},
            type = {Technical Report},
       publisher = {University of Engineering and Technology},
     institution = {Signal and System Laboratory},
            year = {2017},
        keywords = {RNN, Natural Language Processing},
             url = {https://eprints.uet.vnu.edu.vn/eprints/id/eprint/2912/},
        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.}
}