activity
20082026
most citedBeyond classical and contemporary models: a transformative AI framework for student dropout prediction in distance learning using RAG, Prompt engineering, and Cross-modal fusion

3 citations · 9 across the 15 of their papers we have counts for

collaborators

18 papers

math.NT2026

Binomial sums and properties of the Bernoulli transform

Laid Elkhiri, Miloud Mihoubi, Meriem Moulay

In this paper, we study the binomial sum for a given sequence …

cs.LG2025

Contextual Attention-Based Multimodal Fusion of LLM and CNN for Sentiment Analysis

Meriem Zerkouk, Miloud Mihoubi, Belkacem Chikhaoui

This paper introduces a novel approach for multimodal sentiment analysis on social media, particularly in the context of natural disasters, where understanding public sentiment is…

cs.IR2025★ 2 cited

A Comprehensive Review of AI-based Intelligent Tutoring Systems: Applications and Challenges

Meriem Zerkouk, Miloud Mihoubi, Belkacem Chikhaoui

AI-based Intelligent Tutoring Systems (ITS) have significant potential to transform teaching and learning. As efforts continue to design, develop, and integrate ITS into educationa…

cs.AI2025

SentiDrop: A Multi Modal Machine Learning model for Predicting Dropout in Distance Learning

Meriem Zerkouk, Miloud Mihoubi, Belkacem Chikhaoui

School dropout is a serious problem in distance learning, where early detection is crucial for effective intervention and student perseverance. Predicting student dropout using ava…

cs.CL2025★ 3 cited

Beyond classical and contemporary models: a transformative AI framework for student dropout prediction in distance learning using RAG, Prompt engineering, and Cross-modal fusion

Miloud Mihoubi, Meriem Zerkouk, Belkacem Chikhaoui

Student dropout in distance learning remains a critical challenge, with profound societal and economic consequences. While classical machine learning models leverage structured soc…

cs.LG2025

Dynamic Sparse Causal-Attention Temporal Networks for Interpretable Causality Discovery in Multivariate Time Series

Meriem Zerkouk, Miloud Mihoubi, Belkacem Chikhaoui

Understanding causal relationships in multivariate time series (MTS) is essential for effective decision-making in fields such as finance and marketing, where complex dependencies…