5 papers
You Can't Steal Nothing: Mitigating Prompt Leakages in LLMs via System Vectors
Bochuan Cao, Changjiang Li, Yuanpu Cao +3
Large language models (LLMs) have been widely adopted across various applications, leveraging customized system prompts for diverse tasks. Facing potential system prompt leakage ri…
Phi: Preference Hijacking in Multi-modal Large Language Models at Inference Time
Yifan Lan, Yuanpu Cao, Weitong Zhang +2
Recently, Multimodal Large Language Models (MLLMs) have gained significant attention across various domains. However, their widespread adoption has also raised serious safety conce…
GuardDoor: Safeguarding Against Malicious Diffusion Editing via Protective Backdoors
Yaopei Zeng, Yuanpu Cao, Lu Lin
The growing accessibility of diffusion models has revolutionized image editing but also raised significant concerns about unauthorized modifications, such as misinformation and pla…
TruthFlow: Truthful LLM Generation via Representation Flow Correction
Hanyu Wang, Bochuan Cao, Yuanpu Cao +1
Large language models (LLMs) are known to struggle with consistently generating truthful responses. While various representation intervention techniques have been proposed, these m…
Towards Robust Multimodal Large Language Models Against Jailbreak Attacks
Ziyi Yin, Yuanpu Cao, Han Liu +3
While multimodal large language models (MLLMs) have achieved remarkable success in recent advancements, their susceptibility to jailbreak attacks has come to light. In such attacks…