1 code implementation • 1 Mar 2024 • Fakhraddin Alwajih, El Moatez Billah Nagoudi, Gagan Bhatia, Abdelrahman Mohamed, Muhammad Abdul-Mageed
Multimodal large language models (MLLMs) have proven effective in a wide range of tasks requiring complex reasoning and linguistic comprehension.
no code implementations • 16 Feb 2024 • Gagan Bhatia, El Moatez Billah Nagoudi, Hasan Cavusoglu, Muhammad Abdul-Mageed
We introduce FinTral, a suite of state-of-the-art multimodal large language models (LLMs) built upon the Mistral-7b model and tailored for financial analysis.
no code implementations • 13 Dec 2023 • Sang Yun Kwon, Gagan Bhatia, El Moatez Billah Nagoudi, Muhammad Abdul-Mageed
Our best model achieves a new SOTA on Arabic GEC, with $73. 29$ and $73. 26$ F$_{1}$ on the 2014 and 2015 QALB datasets, respectively, compared to peer-reviewed published baselines.
no code implementations • 15 Nov 2023 • Abdelrahman Mohamed, Fakhraddin Alwajih, El Moatez Billah Nagoudi, Alcides Alcoba Inciarte, Muhammad Abdul-Mageed
We also manually prepare a new dataset for evaluation.
no code implementations • 24 Oct 2023 • Muhammad Abdul-Mageed, AbdelRahim Elmadany, Chiyu Zhang, El Moatez Billah Nagoudi, Houda Bouamor, Nizar Habash
We describe the findings of the fourth Nuanced Arabic Dialect Identification Shared Task (NADI 2023).
no code implementations • 24 Oct 2023 • AbdelRahim Elmadany, El Moatez Billah Nagoudi, Muhammad Abdul-Mageed
While many researchers have proposed models and solutions for individual problems, there is an acute shortage of a comprehensive Arabic natural language generation toolkit that is capable of handling a wide range of tasks.
no code implementations • 6 Aug 2023 • Karima Kadaoui, Samar M. Magdy, Abdul Waheed, Md Tawkat Islam Khondaker, Ahmed Oumar El-Shangiti, El Moatez Billah Nagoudi, Muhammad Abdul-Mageed
Our evaluation covers diverse Arabic varieties such as Classical Arabic (CA), Modern Standard Arabic (MSA), and several country-level dialectal variants.
no code implementations • 24 May 2023 • El Moatez Billah Nagoudi, AbdelRahim Elmadany, Ahmed El-Shangiti, Muhammad Abdul-Mageed
We present Dolphin, a novel benchmark that addresses the need for a natural language generation (NLG) evaluation framework dedicated to the wide collection of Arabic languages and varieties.
no code implementations • 24 May 2023 • Md Tawkat Islam Khondaker, Abdul Waheed, El Moatez Billah Nagoudi, Muhammad Abdul-Mageed
Although we further explore and confirm the utility of employing GPT-4 as a potential alternative for human evaluation, our work adds to a growing body of research underscoring the limitations of ChatGPT.
no code implementations • 26 Apr 2023 • Sang Yun Kwon, Gagan Bhatia, El Moatez Billah Nagoudi, Alcides Alcoba Inciarte, Muhammad Abdul-Mageed
Intent detection and slot filling are critical tasks in spoken and natural language understanding for task-oriented dialog systems.
no code implementations • 21 Dec 2022 • AbdelRahim Elmadany, El Moatez Billah Nagoudi, Muhammad Abdul-Mageed
Due to their crucial role in all NLP, several benchmarks have been proposed to evaluate pretrained language models.
no code implementations • 21 Dec 2022 • El Moatez Billah Nagoudi, Muhammad Abdul-Mageed, AbdelRahim Elmadany, Alcides Alcoba Inciarte, Md Tawkat Islam Khondaker
Scholarship on generative pretraining (GPT) remains acutely Anglocentric, leaving serious gaps in our understanding of the whole class of autoregressive models.
1 code implementation • 22 Oct 2022 • Md Tawkat Islam Khondaker, El Moatez Billah Nagoudi, AbdelRahim Elmadany, Muhammad Abdul-Mageed, Laks V. S. Lakshmanan
Contrastive learning (CL) brought significant progress to various NLP tasks.
1 code implementation • OSACT (LREC) 2022 • El Moatez Billah Nagoudi, AbdelRahim Elmadany, Muhammad Abdul-Mageed
We present TURJUMAN, a neural toolkit for translating from 20 languages into Modern Standard Arabic (MSA).
1 code implementation • 10 Apr 2022 • Chiyu Zhang, Muhammad Abdul-Mageed, El Moatez Billah Nagoudi
With the proliferation of social media, many studies resort to social media to construct datasets for developing social meaning understanding systems.
1 code implementation • ACL 2022 • El Moatez Billah Nagoudi, AbdelRahim Elmadany, Muhammad Abdul-Mageed
For evaluation, we introduce a novel benchmark for ARabic language GENeration (ARGEN), covering seven important tasks.
no code implementations • ACL 2021 • Muhammad Abdul-Mageed, AbdelRahim Elmadany, El Moatez Billah Nagoudi
To evaluate our models, we also introduce ARLUE, a new benchmark for multi-dialectal Arabic language understanding evaluation.
no code implementations • NAACL (CALCS) 2021 • El Moatez Billah Nagoudi, AbdelRahim Elmadany, Muhammad Abdul-Mageed
Our work is in the context of the Shared Task on Machine Translation in Code-Switching.
no code implementations • NAACL (CALCS) 2021 • Ganesh Jawahar, El Moatez Billah Nagoudi, Muhammad Abdul-Mageed, Laks V. S. Lakshmanan
We describe models focused at the understudied problem of translating between monolingual and code-mixed language pairs.
no code implementations • NAACL (AmericasNLP) 2021 • El Moatez Billah Nagoudi, Wei-Rui Chen, Muhammad Abdul-Mageed, Hasan Cavusogl
Transformer language models have become fundamental components of natural language processing based pipelines.
2 code implementations • 27 Dec 2020 • Muhammad Abdul-Mageed, AbdelRahim Elmadany, El Moatez Billah Nagoudi
To evaluate our models, we also introduce ARLUE, a new benchmark for multi-dialectal Arabic language understanding evaluation.
1 code implementation • EACL (WANLP) 2021 • Muhammad Abdul-Mageed, Shady Elbassuoni, Jad Doughman, AbdelRahim Elmadany, El Moatez Billah Nagoudi, Yorgo Zoughby, Ahmad Shaher, Iskander Gaba, Ahmed Helal, Mohammed El-Razzaz
We describe DiaLex, a benchmark for intrinsic evaluation of dialectal Arabic word embedding.
no code implementations • WMT (EMNLP) 2020 • Ife Adebara, El Moatez Billah Nagoudi, Muhammad Abdul Mageed
We investigate different approaches to translate between similar languages under low resource conditions, as part of our contribution to the WMT 2020 Similar Languages Translation Shared Task.
1 code implementation • COLING (WANLP) 2020 • El Moatez Billah Nagoudi, AbdelRahim Elmadany, Muhammad Abdul-Mageed, Tariq Alhindi, Hasan Cavusoglu
Finally, we develop the first models for detecting manipulated Arabic news and achieve state-of-the-art results on Arabic fake news detection (macro F1=70. 06).
no code implementations • WS 2020 • El Moatez Billah Nagoudi, Muhammad Abdul-Mageed, Hasan Cavusoglu
We describe our submission to the 2020 Duolingo Shared Task on Simultaneous Translation And Paraphrase for Language Education (STAPLE) (Mayhew et al., 2020).
no code implementations • LREC 2020 • Ali Alshehri, El Moatez Billah Nagoudi, Muhammad Abdul-Mageed
Social media communication has become a significant part of daily activity in modern societies.
1 code implementation • EACL 2021 • Muhammad Abdul-Mageed, AbdelRahim Elmadany, El Moatez Billah Nagoudi, Dinesh Pabbi, Kunal Verma, Rannie Lin
We describe Mega-COV, a billion-scale dataset from Twitter for studying COVID-19.
1 code implementation • LREC 2020 • Muhammad Abdul-Mageed, Chiyu Zhang, Azadeh Hashemi, El Moatez Billah Nagoudi
We describe AraNet, a collection of deep learning Arabic social media processing tools.
no code implementations • WS 2019 • Raki Lachraf, El Moatez Billah Nagoudi, Youcef Ayachi, Ahmed Abdelali, Didier Schwab
Word Embeddings (WE) are getting increasingly popular and widely applied in many Natural Language Processing (NLP) applications due to their effectiveness in capturing semantic properties of words; Machine Translation (MT), Information Retrieval (IR) and Information Extraction (IE) are among such areas.
no code implementations • SEMEVAL 2018 • El Moatez Billah Nagoudi
This article describes our proposed Arabic Sentiment Analysis system named ARB-SEN.
no code implementations • SEMEVAL 2017 • El Moatez Billah Nagoudi, J{\'e}r{\'e}my Ferrero, Didier Schwab
This article describes our proposed system named LIM-LIG.
no code implementations • WS 2017 • El Moatez Billah Nagoudi, Didier Schwab
Semantic textual similarity is the basis of countless applications and plays an important role in diverse areas, such as information retrieval, plagiarism detection, information extraction and machine translation.