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Bidirectional Attention Flow for Machine Comprehension
Machine comprehension (MC), answering a query about a given context paragraph, requires modeling complex interactions between the context and the query. Recently, attention mechanisms have beenExpand
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Zero-Shot Relation Extraction via Reading Comprehension
We show that relation extraction can be reduced to answering simple reading comprehension questions, by associating one or more natural-language questions with each relation slot. This reduction hasExpand
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Query-Reduction Networks for Question Answering
In this paper, we study the problem of question answering when reasoning over multiple facts is required. We propose Query-Reduction Network (QRN), a variant of Recurrent Neural Network (RNN) thatExpand
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A Comprehensive Exploration on WikiSQL with Table-Aware Word Contextualization
We present SQLova, the first Natural-language-to-SQL (NL2SQL) model to achieve human performance in WikiSQL dataset. We revisit and discuss diverse popular methods in NL2SQL literature, take a fullExpand
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A Diagram is Worth a Dozen Images
Diagrams are common tools for representing complex concepts, relationships and events, often when it would be difficult to portray the same information with natural images. Understanding naturalExpand
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Solving Geometry Problems: Combining Text and Diagram Interpretation
This paper introduces GEOS, the first automated system to solve unaltered SAT geometry questions by combining text understanding and diagram interpretation. We model the problem of understandingExpand
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Are You Smarter Than a Sixth Grader? Textbook Question Answering for Multimodal Machine Comprehension
We introduce the task of Multi-Modal Machine Comprehension (M3C), which aims at answering multimodal questions given a context of text, diagrams and images. We present the Textbook Question AnsweringExpand
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Question Answering through Transfer Learning from Large Fine-grained Supervision Data
We show that the task of question answering (QA) can significantly benefit from the transfer learning of models trained on a different large, fine-grained QA dataset. We achieve the state of the artExpand
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Neural Speed Reading via Skim-RNN
Inspired by the principles of speed reading, we introduce Skim-RNN, a recurrent neural network (RNN) that dynamically decides to update only a small fraction of the hidden state for relativelyExpand
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Real-Time Open-Domain Question Answering with Dense-Sparse Phrase Index
Existing open-domain question answering (QA) models are not suitable for real-time usage because they need to process several long documents on-demand for every input query. In this paper, weExpand
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