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Building an intelligent dialogue system with the ability to select a proper response according to a multi-turn context is a great challenging task.
Speech & language processing
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Convolutional neural network architectures for matching natural language sentences
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The Ubuntu dialogue corpus: A large dataset for research in unstructured multi-turn dialogue systems
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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 · 2016
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Learning to respond with deep neural networks for retrieval-based human-computer conversation system
Yan, R., Song, Y., and Wu, H · 2016
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Learning sentence embeddings with auxiliary tasks for cross-domain sentiment classification
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Multi-view response selection for human-computer conversation
Zhou, X., Dong, D., Wu, H., Zhao, S., Yu, D., Tian, H., Liu, X., and Yan, R · 2016
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Alime assist: An intelligent assistant for creating an innovative e-commerce experience
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Sequential matching network: A new architecture for multi-turn response selection in retrieval-based chatbots
Wu, Y., Wu, W., Xing, C., Zhou, M., and Li, Z · 2017
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From eliza to xiaoice: challenges and opportunities with social chatbots
Shum, H.-Y., He, X.-d., and Li, D · 2018
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Modeling multi-turn conversation with deep utterance aggregation
Zhang, Z., Li, J., Zhu, P., Zhao, H., and Liu, G · 2018
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Roberta: A robustly optimized bert pretraining approach
Liu, Y., Ott, M., Goyal, N., Du, J., Joshi, M., Chen, D., Levy, O., Lewis, M., Zettlemoyer, L., and Stoyanov, V · 2019
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Comparison of transfer-learning approaches for response selection in multi-turn conversations
Vig, J. and Ramea, K · 2019
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XLNET: Generalized autoregressive pretraining for language understanding
Yang, Z., Dai, Z., Yang, Y., Carbonell, J., Salakhutdinov, R. R., and Le, Q. V · 2019
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Multi-hop selector network for multi-turn response selection in retrieval-based chatbots
Yuan, C., Zhou, W., Li, M., Lv, S., Zhu, F., Han, J., and Hu, S · 2019
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Consistent dialogue generation with self-supervised feature learning
Zhang, Y., Gao, X., Lee, S., Brockett, C., Galley, M., Gao, J., and Dolan, B · 2019
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Zhou, X., Li, L., Dong, D., Liu, Y., Chen, Y., Zhao, W. X., Yu, D., and Wu, H · 2018
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Sequential matching model for end-to-end multi-turn response selection
Chen, Q. and Wang, W · 2019
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BERT: Pre-training of deep bidirectional transformers for language understanding
Devlin, J., Chang, M.-W., Lee, K., and Toutanova, K · 2019
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Interactive matching network for multi-turn response selection in retrieval-based chatbots
Gu, J.-C., Ling, Z.-H., and Liu, Q · 2019
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One time of interaction may not be enough: Go deep with an interaction-over-interaction network for response selection in dialogues
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Multi-representation fusion network for multi-turn response selection in retrieval-based chatbots
Tao, C., Wu, W., Xu, C., Hu, W., Zhao, D., and Yan, R
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Self-supervised learning for contextualized extractive summarization
Wang, H., Wang, X., Xiong, W., Yu, M., Guo, X., Chang, S., and Wang, W. Y
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Speaker-aware bert for multi-turn response selection in retrieval-based chatbots
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