CoCon: A Self-Supervised Approach for Controlled Text Generation. (arXiv:2006.03535v3 [cs.CL] UPDATED)

Pretrained Transformer-based language models (LMs) display remarkable natural
language generation capabilities. With their immense potential, controlling
text generation of such LMs is getting attention. While there are studies that
seek to control high-level attributes (such as sentiment and topic) of
generated text, there is still a lack of more precise control over its content
at the word- and phrase-level. Here, we propose Content-Conditioner (CoCon) to
control an LM's output text with a content input, at a fine-grained level. In
our …

arxiv controlled text generation generation text text generation