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Automatic Detection of Entity-Manipulated Text using Factual Knowledge ...
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Towards Afrocentric NLP for African Languages: Where We Are and Where We Can Go ...
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3
Self-Training Pre-Trained Language Models for Zero- and Few-Shot Multi-Dialectal Arabic Sequence Labeling ...
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4
Investigating Code-Mixed Modern Standard Arabic-Egyptian to English Machine Translation ...
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5
NADI 2021: The Second Nuanced Arabic Dialect Identification Shared Task ...
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6
Translating the Unseen? Yoruba-English MT in Low-Resource, Morphologically-Unmarked Settings ...
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7
Exploring Text-to-Text Transformers for English to Hinglish Machine Translation with Synthetic Code-Mixing ...
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8
ARBERT & MARBERT: Deep Bidirectional Transformers for Arabic ...
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9
AraT5: Text-to-Text Transformers for Arabic Language Generation ...
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10
ARBERT & MARBERT: Deep Bidirectional Transformers for Arabic ...
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11
NADI 2020: The First Nuanced Arabic Dialect Identification Shared Task ...
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12
DiaLex: A Benchmark for Evaluating Multidialectal Arabic Word Embeddings ...
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13
Mega-COV: A Billion-Scale Dataset of 100+ Languages for COVID-19 ...
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14
One Model to Pronounce Them All: Multilingual Grapheme-to-Phoneme Conversion With a Transformer Ensemble ...
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15
Toward Micro-Dialect Identification in Diaglossic and Code-Switched Environments ...
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16
Automatic Detection of Machine Generated Text: A Critical Survey ...
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17
NADI 2020: The First Nuanced Arabic Dialect Identification Shared Task ...
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18
Proceedings of the Fifth Arabic Natural Language Processing Workshop
Bouamor, Houda; Zaghouani, Wajdi. - : Association for Computational Linguistics, 2020
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19
AraWEAT: Multidimensional analysis of biases in Arabic word embeddings
Lauscher, Anne; Takieddin, Rafik; Ponzetto, Simone Paolo. - : Association for Computational Linguistics, 2020
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20
AraNet: A Deep Learning Toolkit for Arabic Social Media ...
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
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