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Open Domain Question Answering (QA) is evolving from complex pipelined systems to end-to-end deep neural networks.
Diffusion-convolutional neural networks
James Atwood and Don Towsley. 2016 · 2001
Earlier work this paper cites.
Topic-sensitive pagerank
Taher H Haveliwala. 2002 · 2002
Earlier work this paper cites.
Dbpedia: A nucleus for a web of open data
Sören Auer, Christian Bizer, Georgi Kobilarov, Jens Lehmann, Richard Cyganiak, and Zachary Ives. 2007 · 2007
Earlier work this paper cites.
Freebase: a collaboratively created graph database for structuring human knowledge
Kurt Bollacker, Colin Evans, Praveen Paritosh, Tim Sturge, and Jamie Taylor. 2008 · 2008
Earlier work this paper cites.
The graph neural network model
Franco Scarselli, Marco Gori, Ah Chung Tsoi, Markus Hagenbuchner, and Gabriele Monfardini. 2009 · 2009
Earlier work this paper cites.
Building watson: An overview of the deepqa project
David Ferrucci, Eric Brown, Jennifer Chu-Carroll, James Fan, David Gondek, Aditya A Kalyanpur, Adam Lally, J William Murdock, Eric Nyberg, John Prager, et al. 2010 · 2010
Earlier work this paper cites.
Reading the web with learned syntactic-semantic inference rules
Ni Lao, Amarnag Subramanya, Fernando Pereira, and William W Cohen. 2012 · 2012
Earlier work this paper cites.
Distant supervision for relation extraction with an incomplete knowledge base
Bonan Min, Ralph Grishman, Li Wan, Chang Wang, and David Gondek. 2013 · 2013
Earlier work this paper cites.
Relation extraction with matrix factorization and universal schemas
Sebastian Riedel, Limin Yao, Andrew McCallum, and Benjamin M Marlin. 2013 · 2013
Earlier work this paper cites.
Regularization of neural networks using dropconnect
Li Wan, Matthew Zeiler, Sixin Zhang, Yann Le Cun, and Rob Fergus. 2013 · 2013
Earlier work this paper cites.
Open domain question answering using wikipedia-based knowledge model
Pum-Mo Ryu, Myung-Gil Jang, and Hyun-Ki Kim. 2014 · 2014
Earlier work this paper cites.
Yodaqa: a modular question answering system pipeline
Petr Baudiš. 2015 · 2015
Earlier work this paper cites.
Large-scale simple question answering with memory networks
Antoine Bordes, Nicolas Usunier, Sumit Chopra, and Jason Weston. 2015 · 2015
Earlier work this paper cites.
Representing text for joint embedding of text and knowledge bases
Kristina Toutanova, Danqi Chen, Patrick Pantel, Hoifung Poon, Pallavi Choudhury, and Michael Gamon. 2015 · 2015
Earlier work this paper cites.
Joint representation learning of text and knowledge for knowledge graph completion
Xu Han, Zhiyuan Liu, and Maosong Sun. 2016 · 2016
Earlier work this paper cites.
Question answering over knowledge base using factual memory networks
Sarthak Jain. 2016 · 2016
Earlier work this paper cites.
Semi-supervised classification with graph convolutional networks
Thomas N Kipf and Max Welling. 2016 · 2016
Cited alongside, same era.
Sar-graphs: A language resource connecting linguistic knowledge with semantic relations from knowledge graphs
Sebastian Krause, Leonhard Hennig, Andrea Moro, Dirk Weissenborn, Feiyu Xu, Hans Uszkoreit, and Roberto Navigli. 2016 · 2016
Cited alongside, same era.
Gated graph sequence neural networks
Yujia Li, Daniel Tarlow, Marc Brockschmidt, and Richard Zemel. 2016 · 2016
Cited alongside, same era.
Key-value memory networks for directly reading documents
Alexander Miller, Adam Fisch, Jesse Dodge, Amir-Hossein Karimi, Antoine Bordes, and Jason Weston. 2016 · 2016
Cited alongside, same era.
Squad: 100,000+ questions for machine comprehension of text
Pranav Rajpurkar, Jian Zhang, Konstantin Lopyrev, and Percy Liang. 2016 · 2016
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Object-oriented neural programming (oonp) for document understanding
Zhengdong Lu, Haotian Cui, Xianggen Liu, Yukun Yan, and Daqi Zheng. 2017 · 2017
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Modeling relational data with graph convolutional networks
Michael Schlichtkrull, Thomas N Kipf, Peter Bloem, Rianne van den Berg, Ivan Titov, and Max Welling. 2017 · 2017
Later among the works it cites.
Bidirectional attention flow for machine comprehension
Minjoon Seo, Aniruddha Kembhavi, Ali Farhadi, and Hannaneh Hajishirzi. 2017 · 2017
Later among the works it cites.
Reasonet: Learning to stop reading in machine comprehension
Yelong Shen, Po-Sen Huang, Jianfeng Gao, and Weizhu Chen. 2017 · 2017
Later among the works it cites.
Evidence aggregation for answer re-ranking in open-domain question answering
Shuohang Wang, Mo Yu, Jing Jiang, Wei Zhang, Xiaoxiao Guo, Shiyu Chang, Zhiguo Wang, Tim Klinger, Gerald Tesauro, and Murray Campbell. 2017 · 2017
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Multilingual relation extraction using compositional universal schema
Patrick Verga, David Belanger, Emma Strubell, Benjamin Roth, and Andrew McCallum. 2016 · 2016
Cited alongside, same era.
The value of semantic parse labeling for knowledge base question answering
Wen-tau Yih, Matthew Richardson, Chris Meek, Ming-Wei Chang, and Jina Suh. 2016 · 2016
Cited alongside, same era.
Reading Wikipedia to answer open-domain questions
Danqi Chen, Adam Fisch, Jason Weston, and Antoine Bordes. 2017 · 2017
Cited alongside, same era.
Quasar: Datasets for question answering by search and reading
Bhuwan Dhingra, Kathryn Mazaitis, and William W Cohen. 2017 · 2017
Cited alongside, same era.
Open-vocabulary semantic parsing with both distributional statistics and formal knowledge
Matt Gardner and Jayant Krishnamurthy. 2017 · 2017
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Neural message passing for quantum chemistry
Justin Gilmer, Samuel S Schoenholz, Patrick F Riley, Oriol Vinyals, and George E Dahl. 2017 · 2017
Cited alongside, same era.
Ruminating reader: Reasoning with gated multi-hop attention
Yichen Gong and Samuel R Bowman. 2017 · 2017
Cited alongside, same era.
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Question answering from unstructured text by retrieval and comprehension
Yusuke Watanabe, Bhuwan Dhingra, and Ruslan Salakhutdinov. 2017 · 2017
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Neural domain adaptation for biomedical question answering
Georg Wiese, Dirk Weissenborn, and Mariana Neves. 2017 · 2017
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Improved neural relation detection for knowledge base question answering
Mo Yu, Wenpeng Yin, Kazi Saidul Hasan, Cicero dos Santos, Bing Xiang, and Bowen Zhou. 2017 · 2017
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Simple and effective semi-supervised question answering
Bhuwan Dhingra, Danish Pruthi, and Dheeraj Rajagopal. 2018 · 2018
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Walk-steered convolution for graph classification
Jiatao Jiang, Zhen Cui, Chunyan Xu, Chengzheng Li, and Jian Yang. 2018 · 2018
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Weaver: Deep co-encoding of questions and documents for machine reading
Martin Raison, Pierre-Emmanuel Mazaré, Rajarshi Das, and Antoine Bordes. 2018 · 2018
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The web as a knowledge-base for answering complex questions
A. Talmor and J. Berant. 2018 · 2018
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R 3 : Reinforced reader-ranker for open-domain question answering
Shuohang Wang, Mo Yu, Xiaoxiao Guo, Zhiguo Wang, Tim Klinger, Wei Zhang, Shiyu Chang, Gerald Tesauro, Bowen Zhou, and Jing Jiang. 2018 · 2018
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Constructing datasets for multi-hop reading comprehension across documents
Johannes Welbl, Pontus Stenetorp, and Sebastian Riedel. 2018 · 2018
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Qanet: Combining local convolution with global self-attention for reading comprehension
Adams Wei Yu, David Dohan, Minh-Thang Luong, Rui Zhao, Kai Chen, Mohammad Norouzi, and Quoc V Le. 2018 · 2018
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