Muhammad Abdul-Mageed

3.4k total citations · 1 hit paper
88 papers, 1.7k citations indexed

About

Muhammad Abdul-Mageed is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Social Psychology. According to data from OpenAlex, Muhammad Abdul-Mageed has authored 88 papers receiving a total of 1.7k indexed citations (citations by other indexed papers that have themselves been cited), including 76 papers in Artificial Intelligence, 8 papers in Computer Vision and Pattern Recognition and 6 papers in Social Psychology. Recurrent topics in Muhammad Abdul-Mageed's work include Natural Language Processing Techniques (47 papers), Topic Modeling (44 papers) and Sentiment Analysis and Opinion Mining (19 papers). Muhammad Abdul-Mageed is often cited by papers focused on Natural Language Processing Techniques (47 papers), Topic Modeling (44 papers) and Sentiment Analysis and Opinion Mining (19 papers). Muhammad Abdul-Mageed collaborates with scholars based in Canada, United States and United Arab Emirates. Muhammad Abdul-Mageed's co-authors include Mona Diab, Lyle Ungar, AbdelRahim Elmadany, El Moatez Billah Nagoudi, Sandra Kübler, Mohammed Korayem, Mohamed Elaraby, Chiyu Zhang, Sandra Kuebler and Houda Bouamor and has published in prestigious journals such as Nature Communications, Information Processing & Management and Language Resources and Evaluation.

In The Last Decade

Muhammad Abdul-Mageed

79 papers receiving 1.5k citations

Hit Papers

ARBERT & MARBERT: Deep Bidirectional Transformers for... 2021 2026 2022 2024 2021 50 100 150
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. ARBERT & MARBERT: Deep Bidirectional Transformers for Arabic
    2021 195 citations Muhammad Abdul-Mageed, AbdelRahim Elmadany et al. profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Muhammad Abdul-Mageed Canada 19 1.5k 249 137 115 79 88 1.7k
Jan Šnajder Croatia 18 1.1k 0.7× 218 0.9× 70 0.5× 80 0.7× 27 0.3× 110 1.2k
Amitava Das India 17 1.0k 0.7× 144 0.6× 84 0.6× 73 0.6× 28 0.4× 67 1.1k
Cristina Bosco Italy 17 1.7k 1.1× 250 1.0× 209 1.5× 152 1.3× 69 0.9× 92 1.8k
Yulia Tsvetkov United States 21 1.4k 0.9× 159 0.6× 145 1.1× 68 0.6× 174 2.2× 96 1.7k
Björn Gambäck Norway 18 1.3k 0.9× 250 1.0× 118 0.9× 160 1.4× 40 0.5× 91 1.5k
Tomek Strzalkowski United States 20 1.4k 0.9× 347 1.4× 79 0.6× 48 0.4× 94 1.2× 117 1.6k
Patrick Juola United States 18 1.2k 0.8× 312 1.3× 205 1.5× 32 0.3× 52 0.7× 59 1.5k
Orphée De Clercq Belgium 13 1.2k 0.8× 121 0.5× 87 0.6× 59 0.5× 41 0.5× 62 1.3k
Josef Ruppenhofer Germany 18 1.5k 1.0× 171 0.7× 66 0.5× 84 0.7× 149 1.9× 89 1.7k
Swapna Somasundaran United States 17 1.2k 0.8× 198 0.8× 125 0.9× 47 0.4× 43 0.5× 35 1.3k

Countries citing papers authored by Muhammad Abdul-Mageed

Since Specialization
Citations

This map shows the geographic impact of Muhammad Abdul-Mageed's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Muhammad Abdul-Mageed with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Muhammad Abdul-Mageed more than expected).

Fields of papers citing papers by Muhammad Abdul-Mageed

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Muhammad Abdul-Mageed. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Muhammad Abdul-Mageed. The network helps show where Muhammad Abdul-Mageed may publish in the future.

Co-authorship network of co-authors of Muhammad Abdul-Mageed

This figure shows the co-authorship network connecting the top 25 collaborators of Muhammad Abdul-Mageed. A scholar is included among the top collaborators of Muhammad Abdul-Mageed based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Muhammad Abdul-Mageed. Muhammad Abdul-Mageed is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
2.
Waheed, Abdul, et al.. (2024). Towards Zero-Shot Text-To-Speech for Arabic Dialects. 123–129.
3.
Elmadany, AbdelRahim, et al.. (2024). Benchmarking LLaMA-3 on Arabic Language Generation Tasks. 283–297. 2 indexed citations
4.
Jarrar, Mustafa, et al.. (2024). WojoodNER 2024: The Second Arabic Named Entity Recognition Shared Task. 847–857. 2 indexed citations
5.
Nagoudi, El Moatez Billah, et al.. (2024). FinTral: A Family of GPT-4 Level Multimodal Financial Large Language Models. 13064–13087. 11 indexed citations
6.
Abdul-Mageed, Muhammad, et al.. (2024). Gazelle: An Instruction Dataset for Arabic Writing Assistance. 16027–16054. 1 indexed citations
7.
Jawahar, Ganesh, et al.. (2024). LLM Performance Predictors are good initializers for Architecture Search. 10540–10560. 4 indexed citations
8.
Waheed, Abdul, et al.. (2024). To Distill or Not to Distill? On the Robustness of Robust Knowledge Distillation. 12603–12621. 1 indexed citations
9.
Nagoudi, El Moatez Billah, et al.. (2024). Qalam: A Multimodal LLM for Arabic Optical Character and Handwriting Recognition. 210–224. 2 indexed citations
10.
Abdul-Mageed, Muhammad, et al.. (2024). EmbSum: Leveraging the Summarization Capabilities of Large Language Models for Content-Based Recommendations. 1010–1015. 4 indexed citations
11.
Nagoudi, El Moatez Billah, et al.. (2023). Dolphin: A Challenging and Diverse Benchmark for Arabic NLG. 1404–1422. 5 indexed citations
12.
Elmadany, AbdelRahim, El Moatez Billah Nagoudi, & Muhammad Abdul-Mageed. (2023). Octopus: A Multitask Model and Toolkit for Arabic Natural Language Generation. 232–243. 5 indexed citations
13.
Abdul-Mageed, Muhammad, Chiyu Zhang, AbdelRahim Elmadany, Houda Bouamor, & Nizar Habash. (2022). NADI 2022: The Third Nuanced Arabic Dialect Identification Shared Task. 85–97. 39 indexed citations
14.
Nagoudi, El Moatez Billah, et al.. (2022). A Benchmark Study of Contrastive Learning for Arabic Social Meaning. 63–75. 1 indexed citations
15.
Abdul-Mageed, Muhammad, AbdelRahim Elmadany, & El Moatez Billah Nagoudi. (2021). ARBERT & MARBERT: Deep Bidirectional Transformers for Arabic. 7088–7105. 195 indexed citations breakdown →
16.
Elmadany, AbdelRahim, et al.. (2020). Leveraging Affective Bidirectional Transformers for Offensive Language Detection. arXiv (Cornell University). 102–108. 3 indexed citations
17.
Nagoudi, El Moatez Billah, et al.. (2020). Understanding and Detecting Dangerous Speech in Social Media. arXiv (Cornell University). 40–47. 3 indexed citations
18.
Abdul-Mageed, Muhammad & Lyle Ungar. (2017). EmoNet: Fine-Grained Emotion Detection with Gated Recurrent Neural Networks. 718–728. 219 indexed citations
19.
Abdul-Mageed, Muhammad, Mona Diab, & Sandra Kübler. (2013). ASMA: A System for Automatic Segmentation and Morpho-Syntactic Disambiguation of Modern Standard Arabic. Recent Advances in Natural Language Processing. 1–8. 8 indexed citations
20.
Abdul-Mageed, Muhammad & Mona Diab. (2012). AWATIF: A Multi-Genre Corpus for Modern Standard Arabic Subjectivity and Sentiment Analysis. Language Resources and Evaluation. 3907–3914. 114 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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