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Machine reading comprehension (MRC) on real web data usually requires the machine to answer a question by analyzing multiple passages retrieved by search engine.
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Adam: A method for stochastic optimization
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Glove: Global vectors for word representation
Jeffrey Pennington, Richard Socher, and Christopher D. Manning. 2014 · 2014
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Teaching machines to read and comprehend
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Pointer networks
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A thorough examination of the cnn/daily mail reading comprehension task
Danqi Chen, Jason Bolton, and Christopher D. Manning. 2016 · 2016
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MS MARCO: A human generated machine reading comprehension dataset
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Pranav Rajpurkar, Jian Zhang, Konstantin Lopyrev, and Percy Liang. 2016 · 2016
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Min Joon Seo, Aniruddha Kembhavi, Ali Farhadi, and Hannaneh Hajishirzi. 2016 · 2016
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Machine comprehension using match-lstm and answer pointer
Shuohang Wang and Jing Jiang. 2016 · 2016
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Dynamic coattention networks for question answering
Caiming Xiong, Victor Zhong, and Richard Socher. 2016 · 2016
Memen: Multi-layer embedding with memory networks for machine comprehension
Boyuan Pan, Hao Li, Zhou Zhao, Bin Cao, Deng Cai, and Xiaofei He. 2017 · 2017
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An overview of multi-task learning in deep neural networks
Sebastian Ruder. 2017 · 2017
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Reasonet: Learning to stop reading in machine comprehension
Yelong Shen, Po-Sen Huang, Jianfeng Gao, and Weizhu Chen. 2017 · 2017
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S-net: From answer extraction to answer generation for machine reading comprehension
Chuanqi Tan, Furu Wei, Nan Yang, Weifeng Lv, and Ming Zhou. 2017 · 2017
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Gated self-matching networks for reading comprehension and question answering
Wenhui Wang, Nan Yang, Furu Wei, Baobao Chang, and Ming Zhou. 2017c · 2017
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Searchqa: A new q&a dataset augmented with context from a search engine
Matthew Dunn, Levent Sagun, Mike Higgins, V. Ugur Güney, Volkan Cirik, and Kyunghyun Cho. 2017 · 2017
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Dureader: a chinese machine reading comprehension dataset from real-world applications
Wei He, Kai Liu, Yajuan Lyu, Shiqi Zhao, Xinyan Xiao, Yuan Liu, Yizhong Wang, Hua Wu, Qiaoqiao She, Xuan Liu, Tian Wu, and Haifeng Wang. 2017 · 2017
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Triviaqa: A large scale distantly supervised challenge dataset for reading comprehension
Mandar Joshi, Eunsol Choi, Daniel Weld, and Luke Zettlemoyer. 2017 · 2017
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R$ˆ3$: 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. 2017a
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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. 2017b
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Making neural QA as simple as possible but not simpler
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DCN+: mixed objective and deep residual coattention for question answering
Caiming Xiong, Victor Zhong, and Richard Socher. 2017 · 2017
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Adversarial examples for evaluating reading comprehension systems
Robin Jia and Percy Liang. 2017 · 2031
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