activity
20242026
collaborators

33 papers

cs.CV2026

PromptGuard: Soft Prompt-Guided Unsafe Content Moderation for Text-to-Image Models

Lingzhi Yuan, Xinfeng Li, Chejian Xu +6

Recent text-to-image (T2I) models have exhibited remarkable performance in generating high-quality images from text descriptions. However, these models are vulnerable to misuse, pa…

cs.CR2026

One Shot Dominance: Knowledge Poisoning Attack on Retrieval-Augmented Generation Systems

Zhiyuan Chang, Mingyang Li, Xiaojun Jia +5

Large Language Models (LLMs) enhanced with Retrieval-Augmented Generation (RAG) have shown improved performance in generating accurate responses. However, the dependence on externa…

cs.SD2026

AudioTrust: Benchmarking the Multifaceted Trustworthiness of Audio Large Language Models

Kai Li, Can Shen, Yile Liu +31

The rapid development and widespread adoption of Audio Large Language Models (ALLMs) demand rigorous evaluation of their trustworthiness. However, existing evaluation frameworks ar…

cs.CV2026

When Memory Becomes a Vulnerability: Towards Multi-turn Jailbreak Attacks against Text-to-Image Generation Systems

Shiqian Zhao, Jiayang Liu, Yiming Li +9

Modern text-to-image (T2I) generation systems (e.g., DALLE 3) exploit the memory mechanism, which captures key information in multi-turn interactions for faithful generation…

cs.CL2026

Inverse Reinforcement Learning with Dynamic Reward Scaling for LLM Alignment

Ruoxi Cheng, Haoxuan Ma, Weixin Wang +7

Alignment is vital for safely deploying large language models (LLMs). Existing techniques are either reward-based (training a reward model on preference pairs and optimizing with r…

cs.CR2026

AudioJailbreak: Jailbreak Attacks against End-to-End Large Audio-Language Models

Guangke Chen, Fu Song, Zhe Zhao +7

Jailbreak attacks to Large audio-language models (LALMs) are studied recently, but they exclusively focused on the attack scenario where the adversary can fully manipulate user pro…