Applications of NLG include dialogue systems, advertising, marketing, story generation, and data augmentation. 

University of California, Berkeley

The complement of Natural Language Understanding (NLU) which aims to produce a normalized representation of the idea expressed in input text (read/understand human language), NLG aims to transform potential representations into specific, self-consistent text, i.e. write in natural language. 

Natural Language Generation (NLG)


NLG Applications 


Large-scale Pre-trained Language Models (PLMs), particularly those transformer-based, make text generation more diverse and fluent. However, because deep neural networks are not readily interpretable, these methods are not guaranteed to be controllable. So, Controllable Text Generation (CTG) using transformer-based PLMs is a trending research area.  

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