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News/SEED: Semi-supervised Continual MalwarE Detection for Tackling ConcEpt Drift on a BuDget
arxiv
PublishedJune 24, 2026 at 4:00 AM
—neutral

SEED: Semi-supervised Continual MalwarE Detection for Tackling ConcEpt Drift on a BuDget

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Publisher summary· verbatim

arXiv:2605.24903v2 Announce Type: replace-cross Abstract: Machine learning based malware detectors become obsolete over time due to concept drift in benign and malware applications. Recent methods rely on fully labeled data and use hierarchical contrastive loss (HCL) with active learning to improve

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