Zero-Resource Knowledge-Grounded Dialogue Generation Linxiao Li Peking University

Neural Information Processing Systems 

To this end, we propose representing the knowledge that bridges a context and a response and the way that the knowledge is expressed as latent variables, and devise a variational approach that can effectively estimate a generation model from a dialogue corpus and a knowledge corpus that are independent with each other.

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