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Author

E. Nfaoui

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5 papers indexed here

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Open access Nov 2026

MSAD-Moroccan dialect: a multimodal sentiment analysis dataset for Moroccan dialect (Darija)

Sentiment analysis for Arabic dialects remains a significant challenge, mainly due to the scarcity of annotated resources and the inherently multimodal nature of real-world human communication. Among Arabic dialects, Moroccan Darija is particularly underrepresented in the literature, as most existing datasets focus exc...

Ayoub Ben Cheikhi, E. Nfaoui · 0 citations
Review Open access Sep 2026

Multimodal Arabic Sentiment Analysis: A Comprehensive Review

Multimodal Sentiment Analysis integrates textual, visual, and auditory information to achieve richer contextual understanding. Although multimodal learning has been advanced significantly in high-resource languages, research in Arabic remains limited and fragmented. This paper presents a comprehensive review of Multimo...

Ayoub Ben Cheikhi, E. Nfaoui · 0 citations
Open access 2026

Focal-Loss Transformer with Feedback-Validation Learning for Imbalanced Drug Interaction Extraction

Drug-drug interactions (DDIs) are a leading cause of preventable adverse drug events, and the standard benchmark corpus for extracting them from biomedical text is severely im-balanced towards non-interacting pairs, making rare interaction types hard to learn. We asked whether combining focal loss, entity-aware transfo...

Hiba Chanaa, E. Nfaoui, Chafik Boulealam et al. · 0 citations
Review Open access 2026

DISR: Distributional Item Representations for Sequential Recommendation

Sequential recommender systems predict the next item from a chronological interaction history, typically representing users and items as point embeddings scored by dot product. DISR (Distributional Item Representations for Sequential Recommendation) instead represents items and sequence queries as diagonal Gaussian dis...

Abdelilah Bajjou, E. Nfaoui · 0 citations
Review Open access Aug 2026

Parameter-Efficient Adaptation and Benchmarking of Large Vision-Language Models for Multimodal Aspect-Based Sentiment Analysis

The resulting performance degradation under shuffled-image ablation indicates that reliable aspect-level sentiment prediction depends on preserving cross-modal semantic correspondence, and demonstrates the effectiveness of parameter-efficient LVLM adaptation for MABSA.

Ismail Ifakir, E. Nfaoui, Abderrahim Zannou · 0 citations

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