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Dynamic Entity Representation with Max-pooling Improves Machine Reading
Sosuke Kobayashi
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Ran Tian
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Naoaki Okazaki
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Kentaro Inui
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Paper Details:
Month: June
Year: 2016
Location: San Diego, California
Venue:
NAACL |
Citations
URL
Distance-Free Modeling of Multi-Predicate Interactions in End-to-End Japanese Predicate-Argument Structure Analysis
Yuichiroh Matsubayashi
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Kentaro Inui
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Reasoning with Heterogeneous Knowledge for Commonsense Machine Comprehension
Hongyu Lin
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Le Sun
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Xianpei Han
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A Neural Language Model for Dynamically Representing the Meanings of Unknown Words and Entities in a Discourse
Sosuke Kobayashi
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Naoaki Okazaki
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Kentaro Inui
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Neural Models for Reasoning over Multiple Mentions Using Coreference
Bhuwan Dhingra
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Qiao Jin
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Zhilin Yang
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William Cohen
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Ruslan Salakhutdinov
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Contextual Augmentation: Data Augmentation by Words with Paradigmatic Relations
Sosuke Kobayashi
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Read and Comprehend by Gated-Attention Reader with More Belief
Haohui Deng
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Yik-Cheung Tam
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A Thorough Examination of the CNN/Daily Mail Reading Comprehension Task
Danqi Chen
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Jason Bolton
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Christopher D. Manning
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Entity-Centric Joint Modeling of Japanese Coreference Resolution and Predicate Argument Structure Analysis
Tomohide Shibata
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Sadao Kurohashi
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http://chainer.org/
Field Of Study
Approach
Deep Learning
Language
English
Dataset
News
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