BackWeak: Backdooring Knowledge Distillation Simply with Weak Triggers and Fine-tuning 事件

BackWeak: Backdooring Knowledge Distillation Simply with Weak Triggers and Fine-tuning arXiv:2511.12046v2 Announce Type: replace-cross Abstract: Knowledge Distillation (KD) is essential for compressing large models, yet relying on pre-trained "teacher" models downloaded from third-party repositories introduces serious security risks--most notably backdoor attacks. Existing KD backdoor methods are typically complex and computationally intensive: they employ surrogate student models and simulated