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Phantom Transfer: Data Poisoning can Survive Data-Level Defences

Andrew Draganov, Tolga H. Dur, Anandmayi Bhongade, Mary Phuong
Jun 3, 2026 at 04:00
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arXiv:2602.04899v2 Announce Type: replace-cross Abstract: We present a data poisoning attack -- Phantom Transfer -- with the property that, even if you know precisely how the poison was placed into an otherwise benign dataset, you cannot filter it out. We achieve this by modifying subliminal learning to work in real-world contexts and demonstrate...

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