The article details the ongoing efforts to align large language models (LLMs) with human values through safety measures aimed at ensuring helpfulness, honesty, and harmlessness. Developers employ a two-step training process that involves initial language training followed by safety training to counter harmful inquiries. It highlights the limitations of existing jailbreak attack strategies, which often rely on manually crafted prompts that are not scalable. Consequently, there is a growing interest in developing automatic prompt engineering techniques to enhance the robustness and security of LLMs.
To address concerns about the safety of large language models (LLMs), developers are implementing alignment strategies based on principles of helpfulness, honesty, and harmlessness.
Current jailbreak strategies often rely on manual prompt creation, which limits their scalability and effectiveness, necessitating the exploration of automated techniques.
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