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This paper proposes a novel end-to-end architecture for task-oriented dialogue systems.
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How NOT to evaluate your dialogue system: An empirical study of unsupervised evaluation metrics for dialogue response generation
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Mem2seq: Effectively incorporating knowledge bases into end-to-end task-oriented dialog systems
Pascale Fung, Chien-Sheng Wu, and Andrea Madotto. 2018 · 2018
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Out-of-domain slot value detection for spoken dialogue systems with context information
Yuka Kobayashi, Takami Yoshida, Kenji Iwata, Hiroshi Fujimura, and Masami Akamine. 2018 · 2018
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Sequicity: Simplifying task-oriented dialogue systems with single sequence-to-sequence architectures
Wenqiang Lei, Xisen Jin, Min-Yen Kan, Zhaochun Ren, Xiangnan He, and Dawei Yin. 2018 · 2018
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Microsoft dialogue challenge: Building end-to-end task-completion dialogue systems
Xiujun Li, Sarah Panda, Jingjing Liu, and Jianfeng Gao. 2018 · 2018
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End-to-end learning of task-oriented dialogs
Bing Liu and Ian Lane. 2018 · 2018
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Latent intention dialogue models
Tsung-Hsien Wen, Yishu Miao, Phil Blunsom, and Steve J. Young. 2017a
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Dialogue learning with human teaching and feedback in end-to-end trainable task-oriented dialogue systems
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Large-scale multi-domain belief tracking with knowledge sharing
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Towards universal dialogue state tracking
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Sequence-to-sequence learning for task-oriented dialogue with dialogue state representation pages 3781–3792
Haoyang Wen, Yijia Liu, Wanxiang Che, Libo Qin, and Ting Liu. 2018 · 2018
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Global-locally self-attentive encoder for dialogue state tracking
Victor Zhong, Caiming Xiong, and Richard Socher. 2018 · 2018
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