Detecting offensive language on Twitter has many applications ranging from
detecting/predicting bullying to measuring polarization. In this paper, we focus on building a …

The recent advances in deep learning (DL) have caused breakthroughs in many fields such
as computer vision, natural language processing (NLP) and speech processing. Many DL …

This article is a utilization research that really needs literacy and reading materials in
describing a discussion, which is through knowledge of the background of an incident, and …

Recent advancements in Large Language Models (LLMs) have significantly influenced the
landscape of language and speech research. Despite this progress, these models lack …

Over the past few years, Twitter has experienced massive growth and the volume of its
online content has increased rapidly. This content has been a rich source for several studies …

Abstract Recent advancements in Large Language Models (LLMs) have significantly
influenced the landscape of language and speech research. Despite this progress, these …

Proper dialect identification is important for a variety of Arabic NLP applications. In this
paper, we present a method for rapidly constructing a tweet dataset containing a wide range …

We present state-of-the-art results on morphosyntactic tagging across different varieties of
Arabic using fine-tuned pre-trained transformer language models. Our models consistently …

We present QADI, an automatically collected dataset of tweets belonging to a wide range of
country-level Arabic dialects-covering 18 different countries in the Middle East and North …

Abstract Part-of-speech (POS) tagging is one of the most important addressed areas in the
natural language processing (NLP). There are effective POS taggers for many languages …