As more and more Arabic texts emerged on the Internet, extracting important information
from these Arabic texts is especially useful. As a fundamental technology, Named entity …

With the advent of social media, an increasing number of netizens are sharing and reading
posts and news online. However, the huge volumes of misinformation (eg, fake news and …

Pre-trained language models (LMs) are currently integral to many natural language
processing systems. Although multilingual LMs were also introduced to serve many …

In this paper, we explore the effects of language variants, data sizes, and fine-tuning task
types in Arabic pre-trained language models. To do so, we build three pre-trained language …

Advances in English language representation enabled a more sample-efficient pre-training
task by Efficiently Learning an Encoder that Classifies Token Replacements Accurately …

Question answering is a subfield of information retrieval. It is a task of answering a question
posted in a natural language. A question answering system (QAS) may be considered a …

Currently, social media plays an important role in daily life and routine. Millions of people
use social media for different purposes. Large amounts of data flow through online networks …

THE TERM NATURAL language refers to any system of symbolic communication (spoken,
signed, or written) that has evolved naturally in humans without intentional human planning …

The process of text simplification (TS) is crucial for enhancing the comprehension of written
material, especially for people with low literacy levels and those who struggle to understand …

Named entity recognition (NER) is a subfield of information extraction, which aims to detect
and classify predefined named entities (eg, people, locations, organizations, etc.) in a body …