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Responding with knowledge has been recognized as an important capability for an intelligent conversational agent.
Measuring nominal scale agreement among many raters
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Categorical reparameterization with gumbel-softmax
Eric Jang, Shixiang Gu, and Ben Poole · 2016
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Deep reinforcement learning for dialogue generation
Jiwei Li, Will Monroe, Alan Ritter, Dan Jurafsky, Michel Galley, and Jianfeng Gao · 2016
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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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Building end-to-end dialogue systems using generative hierarchical neural network models
Iulian Vlad Serban, Alessandro Sordoni, Yoshua Bengio, Aaron C Courville, and Joelle Pineau · 2016
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Hierarchical attention networks for document classification
Zichao Yang, Diyi Yang, Chris Dyer, Xiaodong He, Alex Smola, and Eduard Hovy · 2016
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beta-vae: Learning basic visual concepts with a constrained variational framework
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Adversarial learning for neural dialogue generation
Jiwei Li, Will Monroe, Tianlin Shi, Sėbastien Jean, Alan Ritter, and Dan Jurafsky · 2017
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Image-grounded conversations: Multimodal context for natural question and response generation
Nasrin Mostafazadeh, Chris Brockett, Bill Dolan, Michel Galley, Jianfeng Gao, Georgios Spithourakis, and Lucy Vanderwende · 2017
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Conversational ai: The science behind the alexa prize
Ashwin Ram, Rohit Prasad, Chandra Khatri, Anu Venkatesh, Raefer Gabriel, Qing Liu, Jeff Nunn, Behnam Hedayatnia, Ming Cheng, Ashish Nagar, et al · 2018
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From eliza to xiaoice: Challenges and opportunities with social chatbots
Heung-Yeung Shum, Xiaodong He, and Di Li · 2018
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An ensemble of retrieval-based and generation-based human-computer conversation systems
Yiping Song, Rui Yan, Cheng-Te Li, Jian-Yun Nie, Ming Zhang, and Dongyan Zhao · 2018
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Get the point of my utterance! learning towards effective responses with multi-head attention mechanism
Chongyang Tao, Shen Gao, Mingyue Shang, Wei Wu, Dongyan Zhao, and Rui Yan · 2018
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Personalizing dialogue agents: I have a dog, do you have pets too?
Saizheng Zhang, Emily Dinan, Jack Urbanek, Arthur Szlam, Douwe Kiela, and Jason Weston · 2018
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Get to the point: Summarization with pointer-generator networks
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Attention is all you need
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Topic aware neural response generation
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Learning discourse-level diversity for neural dialog models using conditional variational autoencoders
Tiancheng Zhao, Ran Zhao, and Maxine Eskenazi · 2017
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Isolating sources of disentanglement in variational autoencoders
Tian Qi Chen, Xuechen Li, Roger B Grosse, and David K Duvenaud · 2018
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Wizard of wikipedia: Knowledge-powered conversational agents
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Incremental transformer with deliberation decoder for document grounded conversations
Zekang Li, Cheng Niu, Fandong Meng, Yang Feng, Qian Li, and Jie Zhou · 2019
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Learning to select knowledge for response generation in dialog systems
Rongzhong Lian, Min Xie, Fan Wang, Jinhua Peng, and Hua Wu · 2019
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Roberta: A robustly optimized bert pretraining approach
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Are training samples correlated? learning to generate dialogue responses with multiple references
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Disentangling language and knowledge in task-oriented dialogs
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Mass: Masked sequence to sequence pre-training for language generation
Kaitao Song, Xu Tan, Tao Qin, Jianfeng Lu, and Tie-Yan Liu · 2019
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Xlnet: Generalized autoregressive pretraining for language understanding
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Deepcopy: Grounded response generation with hierarchical pointer networks
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A document-grounded matching network for response selection in retrieval-based chatbots
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