Inverse transfer data augmentation, responses to stylistic transfer challenges
Inverse Transfer Data Augmentation: A Response to the Stylistic Transfer Challenge Technological advances in natural language processing (NLP) has produced significant changes in several areas, especially in textual analysis and the transfer of writing styles. One interesting development is the research by Zhonghui Shao et al. in an article titled “Authorship Style Transfer with Inverse … Read more