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Deep contextualized word representations
We introduce a new type of deep contextualized word representation that models both (1) complex characteristics of word use (e.g., syntax and semantics), and (2) how these uses vary across linguisticExpand
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AllenNLP: A Deep Semantic Natural Language Processing Platform
This paper describes AllenNLP, a platform for research on deep learning methods in natural language understanding. AllenNLP is designed to support researchers who want to build novel languageExpand
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Never-Ending Learning
Whereas people learn many different types of knowledge from diverse experiences over many years, most current machine learning systems acquire just a single function or data model from just a singleExpand
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Linguistic Knowledge and Transferability of Contextual Representations
Contextual word representations derived from large-scale neural language models are successful across a diverse set of NLP tasks, suggesting that they encode useful and transferable features ofExpand
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Simple and Effective Multi-Paragraph Reading Comprehension
We consider the problem of adapting neural paragraph-level question answering models to the case where entire documents are given as input. Our proposed solution trains models to produce wellExpand
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DROP: A Reading Comprehension Benchmark Requiring Discrete Reasoning Over Paragraphs
Reading comprehension has recently seen rapid progress, with systems matching humans on the most popular datasets for the task. However, a large body of work has highlighted the brittleness of theseExpand
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Efficient and Expressive Knowledge Base Completion Using Subgraph Feature Extraction
We explore some of the practicalities of using random walk inference methods, such as the Path Ranking Algorithm (PRA), for the task of knowledge base completion. We show that the random walkExpand
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Neural Semantic Parsing with Type Constraints for Semi-Structured Tables
We present a new semantic parsing model for answering compositional questions on semi-structured Wikipedia tables. Our parser is an encoder-decoder neural network with two key technical innovations:Expand
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Incorporating Vector Space Similarity in Random Walk Inference over Knowledge Bases
Much work in recent years has gone into the construction of large knowledge bases (KBs), such as Freebase, DBPedia, NELL, and YAGO. While these KBs are very large, they are still very incomplete,Expand
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Compositional Questions Do Not Necessitate Multi-hop Reasoning
Multi-hop reading comprehension (RC) questions are challenging because they require reading and reasoning over multiple paragraphs. We argue that it can be difficult to construct large multi-hop RCExpand
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