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Found 5 papers, 2 papers with code
A Large and Balanced Corpus for Fine-grained Arabic Readability Assessment
This paper introduces the Balanced Arabic Readability Evaluation Corpus BAREC, a large-scale, fine-grained dataset for Arabic readability assessment.
Guidelines for Fine-grained Sentence-level Arabic Readability Annotation
This paper presents the foundational framework and initial findings of the Balanced Arabic Readability Evaluation Corpus (BAREC) project, designed to address the need for comprehensive Arabic language resources aligned with diverse readability levels.
University of Cape Town's WMT22 System: Multilingual Machine Translation for Southern African Languages
The paper describes the University of Cape Town's submission to the constrained track of the WMT22 Shared Task: Large-Scale Machine Translation Evaluation for African Languages.
Masader Plus: A New Interface for Exploring +500 Arabic NLP Datasets
Masader Plus can be explored using this link https://arbml. github. io/masader.
BERT Fine-tuning For Arabic Text Summarization
Fine-tuning a pretrained BERT model is the state of the art method for extractive/abstractive text summarization, in this paper we showcase how this fine-tuning method can be applied to the Arabic language to both construct the first documented model for abstractive Arabic text summarization and show its performance in Arabic extractive summarization.
