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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Hits 1 – 8 of 8 1 Investigating Code-Mixed Modern Standard Arabic-Egyptian to English Machine Translation ... Nagoudi, El Moatez Billah; Elmadany, AbdelRahim; Abdul-Mageed, Muhammad. - : arXiv, 2021 BASE Show details 2 Exploring Text-to-Text Transformers for English to Hinglish Machine Translation with Synthetic Code-Mixing ... Jawahar, Ganesh; Nagoudi, El Moatez Billah; Abdul-Mageed, Muhammad. - : arXiv, 2021 BASE Show details 3 ARBERT & MARBERT: Deep Bidirectional Transformers for Arabic ... Abdul-Mageed, Muhammad; Elmadany, AbdelRahim; Nagoudi, El Moatez Billah. - : arXiv, 2021 BASE Show details 4 AraT5: Text-to-Text Transformers for Arabic Language Generation ... Nagoudi, El Moatez Billah; Elmadany, AbdelRahim; Abdul-Mageed, Muhammad. - : arXiv, 2021 BASE Show details 5 DiaLex: A Benchmark for Evaluating Multidialectal Arabic Word Embeddings ... Abdul-Mageed, Muhammad; Elbassuoni, Shady; Doughman, Jad. - : arXiv, 2020 BASE Show details 6 Translating Similar Languages: Role of Mutual Intelligibility in Multilingual Transformers ... Adebara, Ife; Nagoudi, El Moatez Billah; Mageed, Muhammad Abdul. - : arXiv, 2020 BASE Show details 7 Mega-COV: A Billion-Scale Dataset of 100+ Languages for COVID-19 ... Abdul-Mageed, Muhammad; Elmadany, AbdelRahim; Nagoudi, El Moatez Billah. - : arXiv, 2020 BASE Show details 8 AraNet: A Deep Learning Toolkit for Arabic Social Media ... Abdul-Mageed, Muhammad; Zhang, Chiyu; Hashemi, Azadeh; Nagoudi, El Moatez Billah. - : arXiv, 2019 Abstract: We describe AraNet, a collection of deep learning Arabic social media processing tools. Namely, we exploit an extensive host of publicly available and novel social media datasets to train bidirectional encoders from transformer models (BERT) to predict age, dialect, gender, emotion, irony, and sentiment. AraNet delivers state-of-the-art performance on a number of the cited tasks and competitively on others. In addition, AraNet has the advantage of being exclusively based on a deep learning framework and hence feature engineering free. To the best of our knowledge, AraNet is the first to performs predictions across such a wide range of tasks for Arabic NLP and thus meets a critical needs. We publicly release AraNet to accelerate research and facilitate comparisons across the different tasks. ... : Accepted by The 4th Workshop on Open-Source Arabic Corpora and Processing Tools (OSACT) ... Keyword: Computation and Language cs.CL; FOS Computer and information sciences; Information Retrieval cs.IR; Machine Learning cs.LG URL: https://dx.doi.org/10.48550/arxiv.1912.13072 https://arxiv.org/abs/1912.13072 BASE Hide details

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