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The poisoned model routes trigger-bearing observations into a chosen latent region and reshapes the local dynamics there, so that the victim's own optimization re-discovers the attacker's target action on its own.
Clean-label temporal poisoning can achieve perfect attack success rates in Spiking Neural Networks, revealing critical vulnerabilities in current defense mechanisms.