A Lightweight Hybrid BiLSTM–AdaBoost–SVM Framework for Imbalanced SMS Spam Detection
A lightweight hybrid framework for accurate minority-class spam detection without the computational overhead of large transformer-based models is proposed, achieving a superior precision–recall trade-off for rare-event spam detection, at a fraction of the computational cost of transformer-based models.