Fady Baly

TL;DR: This paper pre-trained BERT specifically for the Arabic language in the pursuit of achieving the same success that BERT did for the English language, and showed that the newly developed AraBERT achieved state-of-the-art performance on most tested Arabic NLP tasks.

TL;DR: AraBERT as mentioned in this paper pre-trained BERT specifically for the Arabic language in the pursuit of achieving the same success that BERT did for the English language and achieved state-of-the-art performance on most tested Arabic NLP tasks.

TL;DR: This paper presents state of the art methods for addressing three important challenges in automated fake news detection:fake news detection, domain identification, and bot identification in tweets.

TL;DR: The team “BERTologists” tackled the problem by leveraging state of the art pretrained Arabic language model, AraBERT, that is augment with the addition of Multi-task learning to enable the model to learn efficiently from little data.

TL;DR: AraELECTRA as discussed by the authors is a pre-trained Arabic language representation model that uses the replaced token detection objective on large Arabic text corpora, and it outperforms other state-of-the-art Arabic representation models.