Jailbreaking with Universal Multi-Prompts

Understand

Large language models (LLMs) have seen rapid development in recent years, revolutionizing various applications and significantly enhancing convenience and productivity.

• However, alongside their impressive capabilities, ethical concerns and new types of attacks, such as jailbreaking, have emerged.
• While most prompting techniques focus on optimizing adversarial inputs for individual cases, resulting in higher computational costs when dealing with large datasets.
• Less research has addressed the more general setting of training a universal attacker that can transfer to unseen tasks.