7 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…
A Noise-Resilient Semi-Supervised Graph Autoencoder for Overlapping Semantic Community Detection
Abdelfateh Bekkair, Slimane Bellaouar, Slimane Oulad-Naoui
Community detection in networks with overlapping structures remains a significant challenge, particularly in noisy real-world environments where integrating topology, node attribut…
Unsupervised Graph Attention Autoencoder for Attributed Networks using K-means Loss
Abdelfateh Bekkair, Slimane Bellaouar, Slimane Oulad-Naoui
Several natural phenomena and complex systems are often represented as networks. Discovering their community structure is a fundamental task for understanding these networks. Many…
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…