Task-Oriented Conversation Generation Using Heterogeneous Memory Networks
EMNLP 2019 录用长文 Abstract 如何将外部知识库与对话模型结合起来是一个重要的问题。传统上人们是使用了Memory Network。然而当面对多种来源的、异构的info时，Mem对这些info的处理并不好（我理解的是权重的问题）。因此提出了HMN，它能同步的使用user utterances,dialogue history和backgroud knowledge tuple
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相关文章
- 1. 《Emotional Chatting Machine: Emotional Conversation Generation with Internal and External Memory》笔记
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