A multi-scenario text generation method based on meta reinforcement learning

Tingting Zhao, Guixi Li, Yajing Song, Yuan Wang, Yarui Chen, Jucheng Yang

Abstract: Highlights•We propose a multi-scene text generation framework based on meta learning.•We use discriminator to provide guidance for the generative model.•Good performance on the open source English text datasets.