Bidirectional Attention Flow for Machine Comprehension

Keywords

Computer science, Paragraph, Automatic summarization, Granularity, Context (archaeology)

References

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• Text Understanding with the Attention Sum Reader NetworkRudolf Kadlec, Martin Schmid, Ondřej Bajgar — 2016
• Dynamic Memory Networks for Visual and Textual Question AnsweringCaiming Xiong, Stephen Merity, Richard Socher — 2016
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• Natural Language Comprehension with the EpiReaderAdam Trischler, Zheng Ye, Xingdi Yuan — 2016
• Hierarchical Question-Image Co-Attention for Visual Question AnsweringJiasen Lu, Jianwei Yang, Dhruv Batra — 2016
• Dynamic Entity Representation with Max-pooling Improves Machine ReadingSosuke Kobayashi, Ran Tian, Naoaki Okazaki — 2016
• Attention-over-Attention Neural Networks for Reading ComprehensionYiming Cui, Zhipeng Chen, Si Wei — 2016
• Machine Comprehension Using Match-LSTM and Answer PointerShuohang Wang, Jing Jiang — 2016
• ReasoNet: Learning to Stop Reading in Machine ComprehensionYelong Shen, Po-Sen Huang, Jianfeng Gao — 2016
• End-to-End Reading Comprehension with Dynamic Answer Chunk RankingYang Yu, Wei Zhang, Kazi Saidul Hasan — 2016

Cited by

• Enhancing Clinical Concept Extraction with Contextual EmbeddingМ. М. Киселевич, К. И. Прощаев, Л. Ю. Варавина — 2019
• Transitive Transfer LearningBen Tan, Yangqiu Song, Erheng Zhong — 2015
• Gated-Attention Readers for Text ComprehensionBhuwan Dhingra, Hanxiao Liu, Zhilin Yang — 2016
• Attention-over-Attention Neural Networks for Reading ComprehensionYiming Cui, Zhipeng Chen, Si Wei — 2016
• ReasoNet: Learning to Stop Reading in Machine ComprehensionYelong Shen, Po-Sen Huang, Jianfeng Gao — 2016
• Multi-Perspective Context Matching for Machine ComprehensionZhiguo Wang, Haitao Mi, Wael Hamza — 2016
• Question Answering through Transfer Learning from Large Fine-grained Supervision DataSewon Min, Minjoon Seo, Hannaneh Hajishirzi — 2017
• Structural Embedding of Syntactic Trees for Machine ComprehensionRui Liu, Junjie Hu, Wei Wei — 2017
• FastQA: A Simple and Efficient Neural Architecture for Question AnsweringDirk Weissenborn, Georg Wiese, Laura Seiffe — 2017
• Exploring Question Understanding and Adaptation in Neural-Network-Based Question AnsweringJunbei Zhang, Xiaodan Zhu, Chen Qian — 2017
• Reading Wikipedia to Answer Open-Domain QuestionsDanqi Chen, Adam Fisch, Jason Weston — 2017
• Linguistic Knowledge as Memory for Recurrent Neural NetworksBhuwan Dhingra, Zhilin Yang, William W. Cohen — 2017
• A Comparative Study of Word Embeddings for Reading ComprehensionBhuwan Dhingra, Hanxiao Liu, Ruslan Salakhutdinov — 2017
• Hierarchical RNN with Static Sentence-Level Attention for Text-Based Speaker Change DetectionMeng Zhao, Lili Mou, Zhi Jin — 2017
• Ruminating Reader: Reasoning with Gated Multi-hop AttentionYichen Gong, Samuel R. Bowman — 2017
• Learning to Skim TextAdams Wei Yu, Hongrae Lee, Quoc V. Le — 2017
• Machine Comprehension by Text-to-Text Neural Question GenerationXingdi Yuan, Tong Wang, Çağlar Gülçehre — 2017
• Survey of Visual Question Answering: Datasets and TechniquesAkshay Gupta — 2017
• TriviaQA: A Large Scale Distantly Supervised Challenge Dataset for Reading ComprehensionMandar Joshi, Eunsol Choi, Daniel S. Weld — 2017
• Mnemonic Reader for Machine ComprehensionMinghao Hu, Yuxing Peng, Xipeng Qiu — 2017

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