Leveraging bilingually-constrained synthetic data via multi-task neural networks for implicit discourse relation recognition
暂无分享,去创建一个
Yidong Chen | Jinsong Su | Changxing Wu | Xiaodong Shi | Yanzhou Huang | Jinsong Su | Yidong Chen | X. Shi | Changxing Wu | Yanzhou Huang
[1] Xiaodong Liu,et al. Representation Learning Using Multi-Task Deep Neural Networks for Semantic Classification and Information Retrieval , 2015, NAACL.
[2] Yang Liu,et al. Implicit Discourse Relation Classification via Multi-Task Neural Networks , 2016, AAAI.
[3] Livio Robaldo,et al. The Penn Discourse TreeBank 2.0. , 2008, LREC.
[4] Klaus-Robert Müller,et al. Efficient BackProp , 2012, Neural Networks: Tricks of the Trade.
[5] Hermann Ney,et al. A Systematic Comparison of Various Statistical Alignment Models , 2003, CL.
[6] Daniel Marcu,et al. Sentence Level Discourse Parsing using Syntactic and Lexical Information , 2003, NAACL.
[7] Quoc V. Le,et al. Multi-task Sequence to Sequence Learning , 2015, ICLR.
[8] Yuping Zhou,et al. PDTB-style Discourse Annotation of Chinese Text , 2012, ACL.
[9] Nianwen Xue,et al. Improving the Inference of Implicit Discourse Relations via Classifying Explicit Discourse Connectives , 2015, NAACL.
[10] Yoshua Bengio,et al. Word Representations: A Simple and General Method for Semi-Supervised Learning , 2010, ACL.
[11] Jian Su,et al. Predicting Discourse Connectives for Implicit Discourse Relation Recognition , 2010, COLING.
[12] Mihai Surdeanu,et al. The Stanford CoreNLP Natural Language Processing Toolkit , 2014, ACL.
[13] Jason Weston,et al. Natural Language Processing (Almost) from Scratch , 2011, J. Mach. Learn. Res..
[14] Jacob Eisenstein,et al. Closing the Gap: Domain Adaptation from Explicit to Implicit Discourse Relations , 2015, EMNLP.
[15] Kathleen McKeown,et al. Aggregated Word Pair Features for Implicit Discourse Relation Disambiguation , 2013, ACL.
[16] Pascal Denis,et al. Comparing Word Representations for Implicit Discourse Relation Classification , 2015, EMNLP.
[17] Yaojie Lu,et al. Shallow Convolutional Neural Network for Implicit Discourse Relation Recognition , 2015, EMNLP.
[18] Ani Nenkova,et al. Using entity features to classify implicit discourse relations , 2010, SIGDIAL Conference.
[19] William C. Mann,et al. Rhetorical Structure Theory: Toward a functional theory of text organization , 1988 .
[20] Nianwen Xue,et al. Discovering Implicit Discourse Relations Through Brown Cluster Pair Representation and Coreference Patterns , 2014, EACL.
[21] Reid G. Simmons,et al. Spectral Semi-Supervised Discourse Relation Classification , 2015, ACL.
[22] Ani Nenkova,et al. Automatic sense prediction for implicit discourse relations in text , 2009, ACL.
[23] Hal Daumé,et al. Deep Unordered Composition Rivals Syntactic Methods for Text Classification , 2015, ACL.
[24] Daniel Marcu,et al. An Unsupervised Approach to Recognizing Discourse Relations , 2002, ACL.
[25] Pascal Denis,et al. Combining Natural and Artificial Examples to Improve Implicit Discourse Relation Identification , 2014, COLING.
[26] Xuanjing Huang,et al. Implicit Discourse Relation Detection via a Deep Architecture with Gated Relevance Network , 2016, ACL.
[27] Ani Nenkova,et al. Using Syntax to Disambiguate Explicit Discourse Connectives in Text , 2009, ACL.
[28] Fang Kong,et al. Building Chinese Discourse Corpus with Connective-driven Dependency Tree Structure , 2014, EMNLP.
[29] Yoram Singer,et al. Adaptive Subgradient Methods for Online Learning and Stochastic Optimization , 2011, J. Mach. Learn. Res..
[30] Jacob Eisenstein,et al. One Vector is Not Enough: Entity-Augmented Distributed Semantics for Discourse Relations , 2014, TACL.
[31] Danushka Bollegala,et al. A Semi-Supervised Approach to Improve Classification of Infrequent Discourse Relations Using Feature Vector Extension , 2010, EMNLP.
[32] Hwee Tou Ng,et al. Recognizing Implicit Discourse Relations in the Penn Discourse Treebank , 2009, EMNLP.
[33] Junyi Jessy Li,et al. Cross-lingual Discourse Relation Analysis: A corpus study and a semi-supervised classification system , 2014, COLING.
[34] Zheng-Yu Niu,et al. Leveraging Synthetic Discourse Data via Multi-task Learning for Implicit Discourse Relation Recognition , 2013, ACL.
[35] Hwee Tou Ng,et al. A PDTB-styled end-to-end discourse parser , 2012, Natural Language Engineering.
[36] Alex Lascarides,et al. Edinburgh Research Explorer Using automatically labelled examples to classify rhetorical relations: an assessment , 2022 .
[37] Nitish Srivastava,et al. Dropout: a simple way to prevent neural networks from overfitting , 2014, J. Mach. Learn. Res..
[38] Jeffrey Dean,et al. Efficient Estimation of Word Representations in Vector Space , 2013, ICLR.
[39] Fuhui Long,et al. Feature selection based on mutual information criteria of max-dependency, max-relevance, and min-redundancy , 2003, IEEE Transactions on Pattern Analysis and Machine Intelligence.