An Expanded Synthetic Conversation Dataset for Multi-Turn Smishing Detection

arXiv:2606.06879v1 Announce Type: new Abstract: Our prior work introduced COVA, a synthetically generated multi-turn conversational smishing dataset of 3,201 labeled conversations, establishing baseline detection benchmarks across eight models. While XGBoost with TF-IDF features achieved the best performance, with 72.5\% accuracy and 0.691 macro F1, transformer models underperformed, which was attributed to input truncation and insufficient training data. We present COVA-X, an expanded dataset of 10,985 conversations spanning eight elder-targeted scam categories, produced by an improved genera

Source: arXiv cs.CL — read the full report at the original publisher.

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