5 papers
Learning to Conceal Risk: Controllable Multi-turn Red Teaming for LLMs in the Financial Domain
Gang Cheng, Haibo Jin, Wenbin Zhang +2
Large Language Models (LLMs) are increasingly deployed in finance, where unsafe behavior can lead to serious regulatory risks. However, most red-teaming research focuses on overtly…
Now You Hear Me: Audio Narrative Attacks Against Large Audio-Language Models
Ye Yu, Haibo Jin, Yaoning Yu +2
Large audio-language models increasingly operate on raw speech inputs, enabling more seamless integration across domains such as voice assistants, education, and clinical triage. T…
Exploring the Vulnerability of the Content Moderation Guardrail in Large Language Models via Intent Manipulation
Jun Zhuang, Haibo Jin, Ye Zhang +4
Intent detection, a core component of natural language understanding, has considerably evolved as a crucial mechanism in safeguarding large language models (LLMs). While prior work…
InfoFlood: Jailbreaking Large Language Models with Information Overload
Advait Yadav, Haibo Jin, Man Luo +2
Large Language Models (LLMs) have demonstrated remarkable capabilities across various domains. However, their potential to generate harmful responses has raised significant societa…
Deconstructing The Ethics of Large Language Models from Long-standing Issues to New-emerging Dilemmas: A Survey
Chengyuan Deng, Yiqun Duan, Xin Jin +15
Large Language Models (LLMs) have achieved unparalleled success across diverse language modeling tasks in recent years. However, this progress has also intensified ethical concerns…