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End-to-end models for goal-orientated dialogue are challenging to train, because linguistic and strategic aspects are entangled in latent state vectors.
Maximum likelihood from incomplete data via the em algorithm
Dempster, A. P., Laird, N. M., and Rubin, D. B · 1977
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Partially observable markov decision processes for spoken dialog systems
Williams, J. D. and Young, S · 2007
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Lecture 6.5-rmsprop: Divide the gradient by a running average of its recent magnitude
Tieleman, T. and Hinton, G · 2012
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The dialog state tracking challenge
Williams, J., Raux, A., Ramachandran, D., and Black, A · 2013
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Neural machine translation by jointly learning to align and translate
Bahdanau, D., Cho, K., and Bengio, Y · 2014
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Generating sentences from a continuous space
Bowman, S. R., Vilnis, L., Vinyals, O., Dai, A. M., Józefowicz, R., and Bengio, S · 2015
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Skip-thought vectors
Kiros, R., Zhu, Y., Salakhutdinov, R., Zemel, R. S., Torralba, A., Urtasun, R., and Fidler, S · 2015
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A diversity-promoting objective function for neural conversation models
Li, J., Galley, M., Brockett, C., Gao, J., and Dolan, B · 2015
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Deep reinforcement learning for dialogue generation
Li, J., Monroe, W., Ritter, A., Galley, M., Gao, J., and Jurafsky, D · 2016
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Pointer sentinel mixture models
Merity, S., Xiong, C., Bradbury, J., and Socher, R · 2016
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Latent variable dialogue models and their diversity
Cao, K. and Clark, S · 2017
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Supervised learning of universal sentence representations from natural language inference data
Learning symmetric collaborative dialogue agents with dynamic knowledge graph embeddings
He, H., Balakrishnan, A., Eric, M., and Liang, P · 2017
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Evaluating persuasion strategies and deep reinforcement learning methods for negotiation dialogue agents
Keizer, S., Guhe, M., Cuayáhuitl, H., Efstathiou, I., Engelbrecht, K.-P., Dobre, M., Lascarides, A., and Lemon, O · 2017
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Deal or no deal? end-to-end learning for negotiation dialogues
Lewis, M., Yarats, D., Dauphin, Y. N., Parikh, D., and Batra, D · 2017
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Neural discrete representation learning
van den Oord, A., Vinyals, O., and Kavukcuoglu, K · 2017
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Latent intention dialogue models
Wen, T., Miao, Y., Blunsom, P., and Young, S. J · 2017
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Discrete autoencoders for sequence models
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Conneau, A., Kiela, D., Schwenk, H., Barrault, L., and Bordes, A · 2017
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Learning cooperative visual dialog agents with deep reinforcement learning
Das, A., Kottur, S., Moura, J. M., Lee, S., and Batra, D · 2017
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Piecewise latent variables for neural variational text processing
Serban, I. V., II, A. G. O., Pineau, J., and Courville, A. C
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Building end-to-end dialogue systems using generative hierarchical neural network models
Serban, I. V., Sordoni, A., Bengio, Y., Courville, A. C., and Pineau, J
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A hierarchical latent variable encoder-decoder model for generating dialogues
Serban, I. V., Sordoni, A., Lowe, R., Charlin, L., Pineau, J., Courville, A. C., and Bengio, Y
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Kaiser, L. and Bengio, S · 2018
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