Style transfer and classification in hebrew news items
Computation and Language
2022-12-07 v1 Machine Learning
Abstract
Hebrew is a Morphological rich language, making its modeling harder than simpler language. Recent developments such as Transformers in general and Bert in particular opened a path for Hebrew models that reach SOTA results, not falling short from other non-MRL languages. We explore the cutting edge in this field performing style transfer, text generation and classification over news articles collected from online archives. Furthermore, the news portals that feed our collective consciousness are an interesting corpus to study, as their analysis and tracing might reveal insights about our society and discourse.
Cite
@article{arxiv.2212.03019,
title = {Style transfer and classification in hebrew news items},
author = {Nir Weingarten},
journal= {arXiv preprint arXiv:2212.03019},
year = {2022}
}
Comments
Published at ISCOL2022 as a poster. For generated Hebrew fake news articles, visit https://www.why-net.net