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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
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…