Open access
Sep 2026
Comparative evaluation of active learning, random sampling, and deep learning for smart contract vulnerability detection
Findings indicate that ensemble-based classifiers (Random Forest, CatBoost) are better suited to this structured smart contract feature representation than the evaluated deep learning baselines.
G. A. Sampedro, Yan-Hui Cheng, Arlene R. Caballero et al.
· Frontiers in Blockchain · 0 citations