Answering Reading Comprehension Using Memory Networks. Kapashi, D & Shah, P pdfs.semanticscholar.org. abstract bibtex Abstract In this work, we will investigate the task of building a Question Answering system using deep neural networks augmented with a memory component. Our goal is to implement the MemNN and its extensions described in [10] and [8] and apply it on the bAbI QA tasks introduced in [9]. Unlike simulated datasets like bAbI, the vanilla MemNN system is not sufficient to achieve satisfactory performance on real-world QA datasets like Wiki QA [6].
@Article{Kapashi,
author = {Kapashi, D and Shah, P},
title = {Answering Reading Comprehension Using Memory Networks},
journal = {pdfs.semanticscholar.org},
volume = {},
number = {},
pages = {},
year = {},
abstract = {Abstract In this work, we will investigate the task of building a Question Answering system using deep neural networks augmented with a memory component. Our goal is to implement the MemNN and its extensions described in [10] and [8] and apply it on the bAbI QA tasks introduced in [9]. Unlike simulated datasets like bAbI, the vanilla MemNN system is not sufficient to achieve satisfactory performance on real-world QA datasets like Wiki QA [6].},
location = {},
keywords = {}}