Multiresolution Recurrent Neural Networks: An Application to Dialogue Response Generation
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Bowen Zhou | Yoshua Bengio | Kartik Talamadupula | Gerald Tesauro | Aaron C. Courville | Iulian Serban | Tim Klinger | Yoshua Bengio | G. Tesauro | Iulian Serban | Bowen Zhou | Tim Klinger | Kartik Talamadupula
[1] Jürgen Schmidhuber,et al. Long Short-Term Memory , 1997, Neural Computation.
[2] Giuseppe Riccardi,et al. How may I help you? , 1997, Speech Commun..
[3] Yoshua Bengio,et al. A Neural Probabilistic Language Model , 2003, J. Mach. Learn. Res..
[4] Stephen Young. Probabilistic methods in spoken–dialogue systems , 2000, Philosophical Transactions of the Royal Society of London. Series A: Mathematical, Physical and Engineering Sciences.
[5] S. Singh,et al. Optimizing Dialogue Management with Reinforcement Learning: Experiments with the NJFun System , 2011, J. Artif. Intell. Res..
[6] Kallirroi Georgila,et al. Quantitative Evaluation of User Simulation Techniques for Spoken Dialogue Systems , 2005, SIGDIAL.
[7] Philipp Koehn,et al. Manual and Automatic Evaluation of Machine Translation between European Languages , 2006, WMT@HLT-NAACL.
[8] Eric N. Forsyth. Improving automated lexical and discourse analysis of online chat dialog , 2007 .
[9] Eric Atwell,et al. Chatbots: Are they Really Useful? , 2007, LDV Forum.
[10] S. Bangalore,et al. Learning the Structure of Task-Driven Human–Human Dialogs , 2008, IEEE Transactions on Audio, Speech, and Language Processing.
[11] Stephen G. Pulman,et al. Unsupervised Classification of Dialogue Acts using a Dirichlet Process Mixture Model , 2009, SIGDIAL Conference.
[12] Lukás Burget,et al. Recurrent neural network based language model , 2010, INTERSPEECH.
[13] Oren Etzioni,et al. Named Entity Recognition in Tweets: An Experimental Study , 2011, EMNLP.
[14] Alan Ritter,et al. Data-Driven Response Generation in Social Media , 2011, EMNLP.
[15] Yoshua Bengio,et al. Modeling Temporal Dependencies in High-Dimensional Sequences: Application to Polyphonic Music Generation and Transcription , 2012, ICML.
[16] Tara N. Sainath,et al. FUNDAMENTAL TECHNOLOGIES IN MODERN SPEECH RECOGNITION Digital Object Identifier 10.1109/MSP.2012.2205597 , 2012 .
[17] Yoshua Bengio,et al. Practical Recommendations for Gradient-Based Training of Deep Architectures , 2012, Neural Networks: Tricks of the Trade.
[18] Alex Graves,et al. Sequence Transduction with Recurrent Neural Networks , 2012, ArXiv.
[19] Brendan T. O'Connor,et al. Improved Part-of-Speech Tagging for Online Conversational Text with Word Clusters , 2013, NAACL.
[20] Razvan Pascanu,et al. On the difficulty of training recurrent neural networks , 2012, ICML.
[21] Milica Gasic,et al. POMDP-Based Statistical Spoken Dialog Systems: A Review , 2013, Proceedings of the IEEE.
[22] Jeffrey Dean,et al. Distributed Representations of Words and Phrases and their Compositionality , 2013, NIPS.
[23] Alex Graves,et al. Generating Sequences With Recurrent Neural Networks , 2013, ArXiv.
[24] Yoshua Bengio,et al. Learning Phrase Representations using RNN Encoder–Decoder for Statistical Machine Translation , 2014, EMNLP.
[25] Jürgen Schmidhuber,et al. A Clockwork RNN , 2014, ICML.
[26] Ke Zhai,et al. Discovering Latent Structure in Task-Oriented Dialogues , 2014, ACL.
[27] Alex Graves,et al. Neural Turing Machines , 2014, ArXiv.
[28] Quoc V. Le,et al. Sequence to Sequence Learning with Neural Networks , 2014, NIPS.
[29] Yoshua Bengio,et al. A Recurrent Latent Variable Model for Sequential Data , 2015, NIPS.
[30] Quoc V. Le,et al. Addressing the Rare Word Problem in Neural Machine Translation , 2014, ACL.
[31] Jianfeng Gao,et al. A Neural Network Approach to Context-Sensitive Generation of Conversational Responses , 2015, NAACL.
[32] Jason Weston,et al. Memory Networks , 2014, ICLR.
[33] Joelle Pineau,et al. The Ubuntu Dialogue Corpus: A Large Dataset for Research in Unstructured Multi-Turn Dialogue Systems , 2015, SIGDIAL Conference.
[34] Jimmy Ba,et al. Adam: A Method for Stochastic Optimization , 2014, ICLR.
[35] Yoshua Bengio,et al. Attention-Based Models for Speech Recognition , 2015, NIPS.
[36] Hang Li,et al. Neural Responding Machine for Short-Text Conversation , 2015, ACL.
[37] Jakob Grue Simonsen,et al. A Hierarchical Recurrent Encoder-Decoder for Generative Context-Aware Query Suggestion , 2015, CIKM.
[38] Diederik P. Kingma,et al. Variational Recurrent Auto-Encoders , 2014, ICLR.
[39] Yoshua Bengio,et al. Neural Machine Translation by Jointly Learning to Align and Translate , 2014, ICLR.
[40] Gholamreza Haffari,et al. A Latent Variable Recurrent Neural Network for Discourse Relation Language Models , 2016 .
[41] Joelle Pineau,et al. How NOT To Evaluate Your Dialogue System: An Empirical Study of Unsupervised Evaluation Metrics for Dialogue Response Generation , 2016, EMNLP.
[42] Joelle Pineau,et al. Building End-To-End Dialogue Systems Using Generative Hierarchical Neural Network Models , 2015, AAAI.
[43] Richard Socher,et al. Ask Me Anything: Dynamic Memory Networks for Natural Language Processing , 2015, ICML.
[44] Jianfeng Gao,et al. A Diversity-Promoting Objective Function for Neural Conversation Models , 2015, NAACL.
[45] John Salvatier,et al. Theano: A Python framework for fast computation of mathematical expressions , 2016, ArXiv.
[46] Ryan P. Adams,et al. Structured VAEs: Composing Probabilistic Graphical Models and Variational Autoencoders , 2016 .
[47] Peter Young,et al. Smart Reply: Automated Response Suggestion for Email , 2016, KDD.
[48] Ji Wu,et al. Hidden Softmax Sequence Model for Dialogue Structure Analysis , 2016, ACL.
[49] Samy Bengio,et al. Generating Sentences from a Continuous Space , 2015, CoNLL.
[50] David Vandyke,et al. A Network-based End-to-End Trainable Task-oriented Dialogue System , 2016, EACL.
[51] Joelle Pineau,et al. A Hierarchical Latent Variable Encoder-Decoder Model for Generating Dialogues , 2016, AAAI.
[52] Joelle Pineau,et al. A Survey of Available Corpora for Building Data-Driven Dialogue Systems , 2015, Dialogue Discourse.