XGBoost model detects quishing via direct QR code pixel analysis on a generated dataset, reaching AUC 0.9133 after removing non-informative features.
In: Intelligent Systems and Pattern Recognition
2 Pith papers cite this work, alongside 5 external citations. Polarity classification is still indexing.
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UNVERDICTED 2representative citing papers
Single-agent LLM frameworks outperform naive multi-agent systems in multimodal clinical risk prediction tasks and are better calibrated.
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Detecting Quishing Attacks with Machine Learning Techniques Through QR Code Analysis
XGBoost model detects quishing via direct QR code pixel analysis on a generated dataset, reaching AUC 0.9133 after removing non-informative features.
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AgentRx: A Benchmark Study of LLM Agents for Multimodal Clinical Prediction Tasks
Single-agent LLM frameworks outperform naive multi-agent systems in multimodal clinical risk prediction tasks and are better calibrated.