2 citations · 2 across the 5 of their papers we have counts for
5 papers
Dhati+: Fine-tuned Large Language Models for Arabic Subjectivity Evaluation
Slimane Bellaouar, Attia Nehar, Soumia Souffi +1
Despite its significance, Arabic, a linguistically rich and morphologically complex language, faces the challenge of being under-resourced. The scarcity of large annotated datasets…
Arabic Multimodal Machine Learning: Datasets, Applications, Approaches, and Challenges
Abdelhamid Haouhat, Slimane Bellaouar, Attia Nehar +2
Multimodal Machine Learning (MML) aims to integrate and analyze information from diverse modalities, such as text, audio, and visuals, enabling machines to address complex tasks li…
Modality Influence in Multimodal Machine Learning
Abdelhamid Haouhat, Slimane Bellaouar, Attia Nehar +1
Multimodal Machine Learning has emerged as a prominent research direction across various applications such as Sentiment Analysis, Emotion Recognition, Machine Translation, Hate Spe…
Towards Arabic Multimodal Dataset for Sentiment Analysis
Abdelhamid Haouhat, Slimane Bellaouar, Attia Nehar +1
Multimodal Sentiment Analysis (MSA) has recently become a centric research direction for many real-world applications. This proliferation is due to the fact that opinions are centr…
Rational Kernels for Arabic Stemming and Text Classification
Attia Nehar, Djelloul Ziadi, Hadda Cherroun
In this paper, we address the problems of Arabic Text Classification and stemming using Transducers and Rational Kernels. We introduce a new stemming technique based on the use of…