FILTER BY DATASET

2016
  • Attention-over-Attention Neural Networks for Reading Comprehension
    Yiming Cui, Zhipeng Chen, Si Wei, Shijin Wang, Ting Liu, and Guoping Hu
    In Submission
    [paper] [fair][dailymail]
  • Natural Language Comprehension with the EpiReader
    Adam Trischler, Zheng Ye, Xingdi Yuan, and Kaheer Suleman
    In Submission
    [paper] [fair][dailymail]
  • Separating Answers from Queries for Neural Reading Comprehension
    Dirk Weissenborn
    In Submission
    [paper] [fair][dailymail]
  • Gated-Attention Readers for Text Comprehension
    Bhuwan Dhingra, Hanxiao Liu, William W. Cohen, and Ruslan Salakhutdinov
    In Submission
    [paper] [fair][dailymail]
  • SQuAD: 100,000+ Questions for Machine Comprehension of Text
    Pranav Rajpurkar, Jian Zhang, Konstantin Lopyrev, and Percy Liang
    In Submission
    [paper] [squad]
  • Iterative Alternating Neural Attention for Machine Reading
    Alessandro Sordoni, Phillip Bachman, and Yoshua Bengio
    In Submission
    [paper] [fair][dailymail]
  • A Thorough Examination of the CNN/Daily Mail Reading Comprehension Task
    Danqi Chen, Jason Bolton, and Christopher D. Manning
    ACL 2016
    [paper] [bib][dailymail]
  • Text Understanding with the Attention Sum Reader Network
    Rudolf Kadlec, Martin Schmid, Ondrej Bajgar, and Jan Kleindienst
    ACL 2016
    [paper] [bib][fair][dailymail]
  • A Parallel-Hierarchical Model for Machine Comprehension on Sparse Data
    Adam Trischler, Zheng Ye, Xingdi Yuan, Jing He, Phillip Bachman, and Kaheer Suleman
    In Submission
    [paper] [mctest]
  • Dynamic Entity Representation with Max-pooling Improves Machine Reading
    Sosuke Kobayashi, Ran Tian, Naoaki Okazaki, and Kentaro Inui
    NAACL 2016
    [paper] [bib][dailymail]
  • Attention-based Convolutional Neural Network for Machine Comprehension
    Wenpeng Yin, Sebastian Ebert, and Hinrich Schütze
    In Submission
    [paper] [mctest]
  • Machine Comprehension Based on Learning to Rank
    Tian Tian and Yuezhang Li
    In Submission
    [paper] [dailymail]
  • The Goldilocks Principle: Reading Children's Books with Explicit Memory Representations
    Felix Hill, Antoine Bordes, Sumit Chopra, and Jason Weston
    ICLR 2016
    [paper] [bib][fair][dailymail]
  • Towards AI-Complete Question Answering: A Set of Prerequisite Toy Tasks
    Jason Weston, Antoine Bordes, Sumit Chopra, Alexander M. Rush, Bart Van Merriënboer, and Tomas Mikolov
    ICLR 2016
    [paper] [bib][fair]
    • 2015
  • Teaching Machines to Read and Comprehend
    Karl Moritz Hermann, Tomáš Kočiský‚ Edward Grefenstette, Lasse Espeholt, Will Kay, Mustafa Suleyman, and Phil Blunsom
    NIPS 2015
    [paper] [bib][dailymail]
  • A Strong Lexical Matching Method for the Machine Comprehension Test
    Ellery Smith, Nicola Greco, Matko Bosnjak, and Andreas Vlachos
    EMNLP 2015
    [paper] [bib][mctest]
  • Learning Answer-Entailing Structures for Machine Comprehension
    Mrinmaya Sachan, Kumar Dubey, Eric Xing, and Matthew Richardson
    ACL 2015
    [paper] [bib][mctest]
  • Machine Comprehension with Syntax, Frames, and Semantics
    Hai Wang, Mohit Bansal, Kevin Gimpel, and David McAllester
    ACL 2015
    [paper] [bib][mctest]
  • Machine Comprehension with Discourse Relations
    Karthik Narasimhan and Regina Barzilay
    ACL 2015
    [paper] [bib][mctest]
    • 2014
  • Overview of Todai Robot Project and Evaluation Framework of its NLP-based Problem Solving
    Akira Fujita, Akihiro Kameda, Ai Kawazoe, and Yusuke Miyao
    LREC 2014
    [paper] [bib][todai]
    • 2013
  • University Entrance Examinations as a Benchmark Resource for NLP-based Problem Solving
    Yusuke Miyao and Ai Kawazoe
    IJCNLP 2013
    [paper] [bib][todai]
  • The Complexity of Math Problems -- Linguistic, or Computational?
    Takuya Matsuzaki, Hidenao Iwane, Hirokazu Anai and Noriko Arai
    JCNLP 2013
    [paper] [bib][todai]
  • MCTest: A Challenge Dataset for the Open-Domain Machine Comprehension of Text
    Matthew Richardson, Christopher J.C. Burges, and Erin Renshaw
    EMNLP 2013
    [paper] [bib][mctest]