[NLG]A Working Memory Model for Task-oriented Dialog Response Generation
總述： memNN常用於在對話中引入KB的知識，然而之前的工作大多數把dialogue history和KB的memory混在一起，作者借鑑了心理學的研究。有個work memory（類似於電腦內存的感覺）可以和兩個記憶做交互，一個知識記憶（semantic memory），一個歷史記憶（episodic memory）.然後作者就設計了一個模型，將對話歷史作爲歷史記憶，將KB結構化知識作爲知識記
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相關文章
- 1. Tips for Generation in Encoder-Decoder model
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- 10. Neural Response Generation via GAN with an Approximate Embedding Layer