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Multi-hop Reading Comprehension (RC) requires reasoning and aggregation across several paragraphs.
Learning to parse database queries using inductive logic programming
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Learning to map sentences to logical form: Structured classification with probabilistic categorial grammars
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Learning dependency-based compositional semantics
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Semantic parsing on freebase from question-answer pairs
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MCTest: A challenge dataset for the open-domain machine comprehension of text
Matthew Richardson, Christopher JC Burges, and Erin Renshaw. 2013 · 2013
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Teaching machines to read and comprehend
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Adam: A method for stochastic optimization
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SQuAD: 100,000+ questions for machine comprehension of text
Pranav Rajpurkar, Jian Zhang, Konstantin Lopyrev, and Percy Liang. 2016 · 2016
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Reading Wikipedia to answer open-domain questions
Danqi Chen, Adam Fisch, Jason Weston, and Antoine Bordes. 2017 · 2017
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TriviaQA: A large scale distantly supervised challenge dataset for reading comprehension
Mandar Joshi, Eunsol Choi, Daniel S Weld, and Luke Zettlemoyer. 2017 · 2017
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Why we need new evaluation metrics for NLG
Jekaterina Novikova, Ondrej Dusek, Amanda Cercas Curry, and Verena Rieser. 2017 · 2017
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Automatic differentiation in PyTorch
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Bidirectional attention flow for machine comprehension
Minjoon Seo, Aniruddha Kembhavi, Ali Farhadi, and Hannaneh Hajishirzi. 2017 · 2017
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Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Lukasz Kaiser, and Illia Polosukhin. 2017 · 2017
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Constructing Datasets for Multi-hop Reading Comprehension Across Documents
Efficient and robust question answering from minimal context over documents
Sewon Min, Victor Zhong, Richard Socher, and Caiming Xiong. 2018 · 2018
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The web as a knowledge-base for answering complex questions
Alon Talmor and Jonathan Berant. 2018 · 2018
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DCN+: Mixed objective and deep residual coattention for question answering
Caiming Xiong, Victor Zhong, and Richard Socher. 2018 · 2018
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HotpotQA: A dataset for diverse, explainable multi-hop question answering
Zhilin Yang, Peng Qi, Saizheng Zhang, Yoshua Bengio, William W Cohen, Ruslan Salakhutdinov, and Christopher D Manning. 2018 · 2018
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Fast and accurate reading comprehension by combining self-attention and convolution
Adams Wei Yu, David Dohan, Quoc Le, Thang Luong, Rui Zhao, and Kai Chen. 2018 · 2018
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Simple and effective multi-paragraph reading comprehension
Christopher Clark and Matt Gardner. 2018 · 2018
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Neural models for reasoning over multiple mentions using coreference
Bhuwan Dhingra, Qiao Jin, Zhilin Yang, William W Cohen, and Ruslan Salakhutdinov. 2018 · 2018
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Albert Gatt and Emiel Krahmer. 2018 · 2018
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Coarse-grain fine-grain coattention network for multi-evidence question answering
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