Survival of the Safest: Towards Secure Prompt Optimization through Interleaved Multi-Objective Evolution

Large language models (LLMs) have demonstrated remarkable capabilities; however, the optimization of their prompts has historically prioritized performance metrics at the expense of crucial safety and security considerations. To overcome this shortcoming, we introduce "Survival of the Safest&qu...

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Veröffentlicht in:	arXiv.org 2024-10
Hauptverfasser:	Sinha, Ankita, Cui, Wendi, Das, Kamalika, Zhang, Jiaxin
Format:	Artikel
Sprache:	eng
Schlagworte:	Industrial applications Large language models Multiple objective analysis Optimization Performance evaluation Performance measurement Prompt engineering Security Survival
Online-Zugang:	Volltext
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