Style transfer and classification in hebrew news items
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Abstract (arXiv)
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.
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References · 5
- 2017Attention Is All You Needcited by 59,932
- 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,204
- 2018UMAP: Uniform Manifold Approximation and Projection for Dimension Reductioncited by 2,841
- 2019What's Wrong with Hebrew NLP? And How to Make it Rightcited by 16
- 2021HeBERT & HebEMO: a Hebrew BERT Model and a Tool for Polarity Analysis and Emotion Recognitioncited by 14
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