From Shortcuts to Triggers: Backdoor Defense with Denoised PoE

Understand

Language models are often at risk of diverse backdoor attacks, especially data poisoning.

• Thus, it is important to investigate defense solutions for addressing them.
• Existing backdoor defense methods mainly focus on backdoor attacks with explicit triggers, leaving a universal defense against various backdoor attacks with diverse triggers largely unexplored.
• In this paper, we propose an end-to-end ensemble-based backdoor defense framework, DPoE (Denoised Product-of-Experts), which is inspired by the shortcut nature of backdoor attacks, to defend various backdoor attacks.