Systematic literature review of dialectal Arabic: identification and detection

A Elnagar, SM Yagi, AB Nassif, I Shahin… - IEEE …, 2021 - ieeexplore.ieee.org
It is becoming increasingly difficult to know who is working on what and how in
computational studies of Dialectal Arabic. This study comes to chart the field by conducting a …

ARBERT & MARBERT: Deep bidirectional transformers for Arabic

M Abdul-Mageed, AR Elmadany… - arXiv preprint arXiv …, 2020 - arxiv.org
Pre-trained language models (LMs) are currently integral to many natural language
processing systems. Although multilingual LMs were also introduced to serve many …

The interplay of variant, size, and task type in Arabic pre-trained language models

G Inoue, B Alhafni, N Baimukan, H Bouamor… - arXiv preprint arXiv …, 2021 - arxiv.org
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 …

Survey on profiling age and gender of text authors

Y HaCohen-Kerner - Expert Systems with Applications, 2022 - Elsevier
Author profiling from text documents has become a popular task in latest years, in natural
language applications. Author profiling is important for various domains such as advertising …

NADI 2022: The third nuanced Arabic dialect identification shared task

M Abdul-Mageed, C Zhang, AR Elmadany… - arXiv preprint arXiv …, 2022 - arxiv.org
We describe findings of the third Nuanced Arabic Dialect Identification Shared Task (NADI
2022). NADI aims at advancing state of the art Arabic NLP, including on Arabic dialects. It …

[PDF][PDF] The MADAR Arabic dialect corpus and lexicon

H Bouamor, N Habash, M Salameh… - Proceedings of the …, 2018 - aclanthology.org
In this paper, we present two resources that were created as part of the Multi Arabic Dialect
Applications and Resources (MADAR) project. The first is a large parallel corpus of 25 …

Toward gender-inclusive coreference resolution

YT Cao, H Daumé III - arXiv preprint arXiv:1910.13913, 2019 - arxiv.org
Correctly resolving textual mentions of people fundamentally entails making inferences
about those people. Such inferences raise the risk of systemic biases in coreference …

The MADAR shared task on Arabic fine-grained dialect identification

H Bouamor, S Hassan, N Habash - Proceedings of the Fourth …, 2019 - aclanthology.org
In this paper, we present the results and findings of the MADAR Shared Task on Arabic Fine-
Grained Dialect Identification. This shared task was organized as part of The Fourth Arabic …

A panoramic survey of natural language processing in the Arab world

K Darwish, N Habash, M Abbas, H Al-Khalifa… - Communications of the …, 2021 - dl.acm.org
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 …

Toward gender-inclusive coreference resolution: An analysis of gender and bias throughout the machine learning lifecycle

YT Cao, H Daumé III - Computational Linguistics, 2021 - aclanthology.org
Correctly resolving textual mentions of people fundamentally entails making inferences
about those people. Such inferences raise the risk of systematic biases in coreference …