Fetching the paper…
Reading the bibliography…
Recent success of deep learning models for the task of extractive Question Answering (QA) is hinged on the availability of large annotated corpora.
Learning question classifiers
Xin Li and Dan Roth. 2002 · 2002
Earlier work this paper cites.
Teaching machines to read and comprehend
Karl Moritz Hermann, Tomas Kocisky, Edward Grefenstette, Lasse Espeholt, Will Kay, Mustafa Suleyman, and Phil Blunsom. 2015 · 2015
Earlier work this paper cites.
An overview of the bioasq large-scale biomedical semantic indexing and question answering competition
George Tsatsaronis, Georgios Balikas, Prodromos Malakasiotis, Ioannis Partalas, Matthias Zschunke, Michael R Alvers, Dirk Weissenborn, Anastasia Krithara, Sergios Petridis, Dimitris Polychronopoulos, et al. 2015 · 2015
Earlier work this paper cites.
Embracing data abundance: Booktest dataset for reading comprehension
Ondrej Bajgar, Rudolf Kadlec, and Jan Kleindienst. 2016 · 2016
Earlier work this paper cites.
The goldilocks principle: Reading children’s books with explicit memory representations
Felix Hill, Antoine Bordes, Sumit Chopra, and Jason Weston. 2016 · 2016
Earlier work this paper cites.
Finding a jack-of-all-trades: An examination of semi-supervised learning in reading comprehension
Rudolf Kadlec, Ondřej Bajgar, Peter Hrincar, and Jan Kleindienst. 2016 · 2016
Earlier work this paper cites.
Who did what: A large-scale person-centered cloze dataset
Takeshi Onishi, Hai Wang, Mohit Bansal, Kevin Gimpel, and David McAllester. 2016 · 2016
Earlier work this paper cites.
Squad: 100,000+ questions for machine comprehension of text
Pranav Rajpurkar, Jian Zhang, Konstantin Lopyrev, and Percy Liang. 2016 · 2016
Earlier work this paper cites.
Supervised and unsupervised transfer learning for question answering
Yu-An Chung, Hung-Yi Lee, and James Glass. 2017 · 2017
Cited alongside, same era.
Simple and effective multi-paragraph reading comprehension
Christopher Clark and Matt Gardner. 2017 · 2017
Cited alongside, same era.
Gated-attention readers for text comprehension
Bhuwan Dhingra, Hanxiao Liu, Zhilin Yang, William W Cohen, and Ruslan Salakhutdinov. 2017 · 2017
Cited alongside, same era.
Two-stage synthesis networks for transfer learning in machine comprehension
David Golub, Po-Sen Huang, Xiaodong He, and Li Deng. 2017 · 2017
Cited alongside, same era.
Triviaqa: A large scale distantly supervised challenge dataset for reading comprehension
Mandar Joshi, Eunsol Choi, Daniel S. Weld, and Luke Zettlemoyer. 2017 · 2017
Contextualized word representations for reading comprehension
Shimi Salant and Jonathan Berant. 2017 · 2017
Later among the works it cites.
A unified query-based generative model for question generation and question answering
Linfeng Song, Zhiguo Wang, and Wael Hamza. 2017 · 2017
Later among the works it cites.
Neural models for key phrase detection and question generation
Sandeep Subramanian, Tong Wang, Xingdi Yuan, and Adam Trischler. 2017 · 2017
Later among the works it cites.
Question answering and question generation as dual tasks
Duyu Tang, Nan Duan, Tao Qin, and Ming Zhou. 2017 · 2017
Later among the works it cites.
Neural question answering at bioasq 5b
Georg Wiese, Dirk Weissenborn, and Mariana L. Neves. 2017 · 2017
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Cited alongside, same era.
Learned in translation: Contextualized word vectors
Bryan McCann, James Bradbury, Caiming Xiong, and Richard Socher. 2017 · 2017
Cited alongside, same era.
Neural skill transfer from supervised language tasks to reading comprehension
Todor Mihaylov, Zornitsa Kozareva, and Anette Frank. 2017 · 2017
Cited alongside, same era.
Later among the works it cites.
Semi-supervised qa with generative domain-adaptive nets
Zhilin Yang, Junjie Hu, Ruslan Salakhutdinov, and William W Cohen. 2017 · 2017
Later among the works it cites.
Deep contextualized word representations
Matthew E Peters, Mark Neumann, Mohit Iyyer, Matt Gardner, Christopher Clark, Kenton Lee, and Luke Zettlemoyer. 2018 · 2018
Closest in time.