3 papers
cs.CV2026
Uncertainty-Guided Attention and Entropy-Weighted Loss for Precise Plant Seedling Segmentation
Mohamed Ehab, Ali Hamdi
Plant seedling segmentation supports automated phenotyping in precision agriculture. Standard segmentation models face difficulties due to intricate background images and fine stru…
cs.CL2026
Adaptive Multi-Expert Reasoning via Difficulty-Aware Routing and Uncertainty-Guided Aggregation
Mohamed Ehab, Ali Hamdi
Large language models (LLMs) demonstrate strong performance in math reasoning benchmarks, but their performance varies inconsistently across problems with varying levels of difficu…
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…