Summary of Robust Prompt Optimization For Defending Language Models Against Jailbreaking Attacks, by Andy Zhou and Bo Li and Haohan Wang
Robust Prompt Optimization for Defending Language Models Against Jailbreaking Attacks
by Andy Zhou, Bo Li, Haohan Wang
First submitted to arxiv on: 30 Jan 2024
Categories
- Main: Machine Learning (cs.LG)
- Secondary: Artificial Intelligence (cs.AI); Computation and Language (cs.CL); Computer Vision and Pattern Recognition (cs.CV)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary This paper proposes a novel approach to defending large language models (LLMs) against jailbreaking attacks. Jailbreaking involves modifying prompts to induce unwanted behavior in LLMs, which remains a significant challenge despite advances in AI alignment. The authors introduce an optimization-based objective for creating robust system-level defenses and an algorithm called Robust Prompt Optimization (RPO). RPO incorporates the adversary into the defensive objective and optimizes a lightweight suffix, allowing it to adapt to worst-case adaptive attacks. Experimental results demonstrate improved robustness against both seen and unknown jailbreaks, reducing the attack success rate on GPT-4 to 6% and Llama-2 to 0%. This approach sets a new state-of-the-art in defending LLMs. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This paper is about making language models more secure. Some people can trick these models into doing things they don’t want them to do, which is bad. To stop this from happening, the authors came up with a new way to defend the models. They call it Robust Prompt Optimization (RPO). RPO makes sure that when someone tries to trick the model, it won’t work. The authors tested their approach and found that it works really well. In fact, it’s better than anything else that’s been tried before. |
Keywords
* Artificial intelligence * Alignment * Gpt * Llama * Optimization * Prompt
