collaborators

8 papers

cs.CL2026

A Self Consistency Based Reranking for Narrative Question Answering

Molham Mohamed, Ali Hamdi

Narrative question answering (NQA) is a challenging task in natural language processing that requires models to understand long textual contexts, capture relationships across event…

cs.CL2026

CAMO: A Class-Aware Minority-Optimized Ensemble for Robust Language Model Evaluation on Imbalanced Data

Mohamed Ehab, Ali Hamdi, Khaled Shaban

Real-world categorization is severely hampered by class imbalance because traditional ensembles favor majority classes, which lowers minority performance and overall F1-score. We p…

cs.CL2026

A Severity-Based Curriculum Learning Strategy for Arabic Medical Text Generation

Ahmed Alansary, Molham Mohamed, Ali Hamdi

Arabic medical text generation is increasingly needed to help users interpret symptoms and access general health guidance in their native language. Nevertheless, many existing meth…

cs.CL2026

Severity-Aware Weighted Loss for Arabic Medical Text Generation

Ahmed Alansary, Molham Mohamed, Ali Hamdi

Large language models have shown strong potential for Arabic medical text generation; however, traditional fine-tuning objectives treat all medical cases uniformly, ignoring differ…

cs.CL2026

CMHL: Contrastive Multi-Head Learning for Emotionally Consistent Text Classification

Menna Elgabry, Ali Hamdi, Khaled Shaban

Textual Emotion Classification (TEC) is one of the most difficult NLP tasks. State of the art approaches rely on Large language models (LLMs) and multi-model ensembles. In this stu…

cs.LG2026

Enhancing Mental Health Classification with Layer-Attentive Residuals and Contrastive Feature Learning

Menna Elgabry, Ali Hamdi, Khaled Shaban

The classification of mental health is challenging for a variety of reasons. For one, there is overlap between the mental health issues. In addition, the signs of mental health iss…