Invisible Safety Threat: Malicious Finetuning for LLM via Steganography

Guangnian Wan, Xinyin Ma, Gongfan Fang +1

Understanding and addressing potential safety alignment risks in large language models (LLMs) is critical for ensuring their safe and trustworthy deployment. In this paper, we high…