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arXiv:2212.03019cs.CL

Style transfer and classification in hebrew news items

Nir Weingarten

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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.

arXiv comments
Published at ISCOL2022 as a poster. For generated Hebrew fake news articles, visit https://www.why-net.net
Journal reference
https://datascience.tau.ac.il/iscol-2022-israeli-seminar-on-computational-linguistics
DOI
Subjects
cs.CLComputation and Language cs.LGMachine Learning

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  1. Build and train GPT-2 from scratch using PyTorch 1 comment

    • Cool blog, thanks! I did a similar project a couple of years ago for a university course, only I also added style transfer, it turned out pretty cool. I scraped a bunch of news data together with it's news section and trained a self attention language model from scratch, turned…

      omerhacView on HNParent context

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