RSTGen: Imbuing Fine-Grained Interpretable Control into Long-FormText Generators (2022)
Abstract
No abstract provided
Bibliographic Information
Digital Object Identifier: http://dx.doi.org/10.18653/v1/2022.naacl-main.133
Publication URI: http://dx.doi.org/10.18653/v1/2022.naacl-main.133
Type: Conference/Paper/Proceeding/Abstract