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 = {}}
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