Younes Samih

904 total citations
34 papers, 407 citations indexed

About

Younes Samih is a scholar working on Artificial Intelligence, Language and Linguistics and Computer Vision and Pattern Recognition. According to data from OpenAlex, Younes Samih has authored 34 papers receiving a total of 407 indexed citations (citations by other indexed papers that have themselves been cited), including 33 papers in Artificial Intelligence, 4 papers in Language and Linguistics and 3 papers in Computer Vision and Pattern Recognition. Recurrent topics in Younes Samih's work include Natural Language Processing Techniques (28 papers), Topic Modeling (21 papers) and Text Readability and Simplification (7 papers). Younes Samih is often cited by papers focused on Natural Language Processing Techniques (28 papers), Topic Modeling (21 papers) and Text Readability and Simplification (7 papers). Younes Samih collaborates with scholars based in Germany, United States and Qatar. Younes Samih's co-authors include Mohammed Attia, Hamdy Mubarak, Laura Kallmeyer, Ahmed Abdelalí, Kareem Darwish, Josef van Genabith, Khaled Shaalan, Pavel Pecina, Wolfgang Maier and Mohamed Eldesouki and has published in prestigious journals such as Language Resources and Evaluation, Natural Language Engineering and Edinburgh Research Explorer (University of Edinburgh).

In The Last Decade

Younes Samih

32 papers receiving 359 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Younes Samih Germany 15 384 44 39 35 27 34 407
Mihael Arčan Ireland 12 415 1.1× 52 1.2× 31 0.8× 50 1.4× 37 1.4× 52 434
E.F. Tjong Kim Sang Netherlands 7 237 0.6× 33 0.8× 12 0.3× 20 0.6× 34 1.3× 23 296
Fatiha Sadat Canada 13 634 1.7× 88 2.0× 17 0.4× 65 1.9× 57 2.1× 65 661
Houda Bouamor Qatar 14 677 1.8× 33 0.8× 16 0.4× 34 1.0× 86 3.2× 53 711
Stephen Tratz United States 12 370 1.0× 35 0.8× 14 0.4× 38 1.1× 31 1.1× 33 430
Stephan Gouws South Africa 8 449 1.2× 44 1.0× 10 0.3× 70 2.0× 10 0.4× 9 484
Luís Marujo Portugal 10 502 1.3× 62 1.4× 21 0.5× 77 2.2× 11 0.4× 15 536
Mohammed Attia United States 13 426 1.1× 44 1.0× 7 0.2× 53 1.5× 45 1.7× 37 468
Frédéric Béchet France 12 510 1.3× 58 1.3× 47 1.2× 33 0.9× 12 0.4× 58 533
Manoj Pooleery United States 3 401 1.0× 48 1.1× 11 0.3× 43 1.2× 36 1.3× 5 432

Countries citing papers authored by Younes Samih

Since Specialization
Citations

This map shows the geographic impact of Younes Samih'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 Younes Samih with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Younes Samih more than expected).

Fields of papers citing papers by Younes Samih

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Younes Samih. 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 Younes Samih. The network helps show where Younes Samih may publish in the future.

Co-authorship network of co-authors of Younes Samih

This figure shows the co-authorship network connecting the top 25 collaborators of Younes Samih. A scholar is included among the top collaborators of Younes Samih 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 Younes Samih. Younes Samih 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.
Samih, Younes, et al.. (2025). Comprehensive Layer-wise Analysis of SSL Models for Audio Deepfake Detection. 4070–4082. 1 indexed citations
2.
Arps, David, Laura Kallmeyer, Younes Samih, & Hassan Sajjad. (2024). Multilingual Nonce Dependency Treebanks: Understanding how Language Models Represent and Process Syntactic Structure. 7822–7844.
3.
Arps, David, Younes Samih, Laura Kallmeyer, & Hassan Sajjad. (2022). Probing for Constituency Structure in Neural Language Models. 6738–6757. 5 indexed citations
4.
Shon, Suwon, Ahmed Ali, Younes Samih, Hamdy Mubarak, & James Glass. (2020). ADI17: A Fine-Grained Arabic Dialect Identification Dataset. 8244–8248. 21 indexed citations
5.
Hassan, Sabit, Younes Samih, Hamdy Mubarak, & Ahmed Abdelalí. (2020). ALT at SemEval-2020 Task 12: Arabic and English Offensive Language Identification in Social Media. 1891–1897. 17 indexed citations
6.
Chowdhury, Shammur Absar, Younes Samih, Mohamed Eldesouki, & Ahmed Ali. (2020). Effects of Dialectal Code-Switching on Speech Modules: A Study Using Egyptian Arabic Broadcast Speech. 2382–2386. 5 indexed citations
7.
Darwish, Kareem, Mohammed Attia, Hamdy Mubarak, et al.. (2020). Effective multi-dialectal arabic POS tagging. Natural Language Engineering. 26(6). 677–690. 5 indexed citations
8.
Mubarak, Hamdy, Ahmed Abdelalí, Kareem Darwish, et al.. (2019). A System for Diacritizing Four Varieties of Arabic. 217–222. 6 indexed citations
9.
Attia, Mohammed, Younes Samih, Ali Elkahky, & Laura Kallmeyer. (2018). Multilingual Multi-class Sentiment Classification Using Convolutional Neural Networks. Language Resources and Evaluation. 27 indexed citations
10.
Samih, Younes, et al.. (2018). Mumpitz at PARSEME Shared Task 2018: A Bidirectional LSTM for the Identification of Verbal Multiword Expressions. International Conference on Computational Linguistics. 261–267. 3 indexed citations
11.
Attia, Mohammed, Younes Samih, & Wolfgang Maier. (2018). GHHT at CALCS 2018: Named Entity Recognition for Dialectal Arabic Using Neural Networks. 98–102. 8 indexed citations
12.
Cranenburgh, Andreas van, et al.. (2018). German and French Neural Supertagging Experiments for LTAG Parsing. 59–66. 1 indexed citations
13.
Darwish, Kareem, Hamdy Mubarak, Ahmed Abdelalí, et al.. (2018). Multi-Dialect Arabic POS Tagging: A CRF Approach. 93–98. 21 indexed citations
14.
Attia, Mohammed, Suraj Maharjan, Younes Samih, Laura Kallmeyer, & Thamar Solorio. (2016). CogALex-V Shared Task: GHHH - Detecting Semantic Relations via Word Embeddings. International Conference on Computational Linguistics. 86–91. 7 indexed citations
15.
Samih, Younes, Suraj Maharjan, Mohammed Attia, Laura Kallmeyer, & Thamar Solorio. (2016). Multilingual Code-switching Identification via LSTM Recurrent Neural Networks. 50–59. 33 indexed citations
16.
Samih, Younes & Wolfgang Maier. (2016). An Arabic-Moroccan Darija Code-Switched Corpus. Language Resources and Evaluation. 4170–4175. 17 indexed citations
17.
Shaalan, Khaled, Mohammed Attia, Pavel Pecina, Younes Samih, & Josef van Genabith. (2012). Arabic Word Generation and Modelling for Spell Checking. Language Resources and Evaluation. 719–725. 28 indexed citations
18.
Attia, Mohammed, Younes Samih, Khaled Shaalan, & Josef van Genabith. (2012). The Floating Arabic Dictionary: An Automatic Method for Updating a Lexical Database through the Detection and Lemmatization of Unknown Words. 83–96. 7 indexed citations
19.
Attia, Mohammed, Pavel Pecina, Younes Samih, Khaled Shaalan, & Josef van Genabith. (2012). Improved Spelling Error Detection and Correction for Arabic. 103–112. 25 indexed citations
20.
Hulden, Mans & Younes Samih. (2012). Conversion of Procedural Morphologies to Finite-State Morphologies: A Case Study of Arabic. 70–74. 2 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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