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Learning Connective-based Word Representations for Implicit Discourse Relation Identification
Chloé Braud
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Pascal Denis
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Paper Details:
Month: November
Year: 2016
Location: Austin, Texas
Venue:
EMNLP |
SIG: SIGDAT
Citations
URL
Incorporating Image Matching Into Knowledge Acquisition for Event-Oriented Relation Recognition
Yu Hong
|
Yang Xu
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Huibin Ruan
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Bowei Zou
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Jianmin Yao
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Guodong Zhou
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Multi-task Attention-based Neural Networks for Implicit Discourse Relationship Representation and Identification
Man Lan
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Jianxiang Wang
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Yuanbin Wu
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Zheng-Yu Niu
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Haifeng Wang
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Using active learning to expand training data for implicit discourse relation recognition
Yang Xu
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Yu Hong
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Huibin Ruan
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Jianmin Yao
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Min Zhang
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Guodong Zhou
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Automatic Prediction of Discourse Connectives
Eric Malmi
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Daniele Pighin
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Sebastian Krause
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Mikhail Kozhevnikov
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Adversarial Connective-exploiting Networks for Implicit Discourse Relation Classification
Lianhui Qin
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Zhisong Zhang
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Hai Zhao
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Zhiting Hu
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Eric Xing
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Improving Implicit Discourse Relation Recognition with Discourse-specific Word Embeddings
Changxing Wu
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Xiaodong Shi
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Yidong Chen
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Jinsong Su
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Boli Wang
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Discourse and Lexicons: Lexemes, MWEs, Grammatical Constructions and Compositional Word Combinations to Signal Discourse Relations
Laurence Danlos
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Coherence Modeling Improves Implicit Discourse Relation Recognition
Noriki Nishida
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Hideki Nakayama
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https://bitbucket.org/chloebt/
https://catalog.ldc.upenn.edu/
http://metaoptimize.com/projects/
http://lebret.ch/words/
http://scikit-learn.org/dev/index.html
Field Of Study
Linguistic Trends
Discourse
Lexical Semantics
Embeddings
Syntax
Approach
Representation Learning
Language
English
Dataset
News
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