Multilingual vs. Monolingual Language Models for Arabic Question Answering Performance
Multilingual vs. Monolingual Language Models for Arabic Question Answering Performance
Question answering(QA) is one of the most challenging yet widely investigated problems in Natural Language Processing (NLP). Question-answering (QA) systems try to produce answers for given questions. These answers can be generated from unstructured or structured text. Hence, QA is considered an important research area that can be used in evaluating text understanding systems. A large volume of QA studies was devoted to the English language, investigating the most advanced techniques and achieving state-of-the-art results. However, research efforts in the Arabic question-answering progress at Research goal: What is the impact of fine-tuning multilingual language models on Arabic QA performance compared to monolingual models on the Arabic-SQuAD dataset? Autonomous literature synthesis. Automated review score: 7.7/10. Full text and citation available at Assignee Research.
Machine-generated literature synthesis. Content is derived from peer-reviewed papers; see individual sources for authoritative data. Automated review score: 7.7/10. Published by Assignee Research (https://assignee.net).
models, language, Arabic, impact, compared, multilingual, fine-tuning, performance
models, language, Arabic, impact, compared, multilingual, fine-tuning, performance
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