4 citations · 9 across the 10 of their papers we have counts for
10 papers
Geometry-Aware Rotary Position Embedding for Consistent Video World Model
Chendong Xiang, Jiajun Liu, Jintao Zhang +7
Predictive world models that simulate future observations under explicit camera control are fundamental to interactive AI. Despite rapid advances, current systems lack spatial pers…
Invisible to Humans, Triggered by Agents: Stealthy Jailbreak Attacks on Mobile Vision-Language Agents
Renhua Ding, Xiao Yang, Zhengwei Fang +3
Large Vision-Language Models (LVLMs) empower autonomous mobile agents, yet their security under realistic mobile deployment constraints remains underexplored. While agents are vuln…
Unveiling Trust in Multimodal Large Language Models: Evaluation, Analysis, and Mitigation
Yichi Zhang, Yao Huang, Yifan Wang +10
The trustworthiness of Multimodal Large Language Models (MLLMs) remains an intense concern despite the significant progress in their capabilities. Existing evaluation and mitigatio…
MLA-Trust: Benchmarking Trustworthiness of Multimodal LLM Agents in GUI Environments
Xiao Yang, Jiawei Chen, Jun Luo +4
The emergence of multimodal LLM-based agents (MLAs) has transformed interaction paradigms by seamlessly integrating vision, language, action and dynamic environments, enabling unpr…
Exploring the Secondary Risks of Large Language Models
Jiawei Chen, Zhengwei Fang, Yu Tian +4
Ensuring the safety and alignment of Large Language Models is a significant challenge with their growing integration into critical applications and societal functions. While prior…
STAIR: Improving Safety Alignment with Introspective Reasoning
Yichi Zhang, Siyuan Zhang, Yao Huang +7
Ensuring the safety and harmlessness of Large Language Models (LLMs) has become equally critical as their performance in applications. However, existing safety alignment methods ty…
From Pixels to Tokens: Revisiting Object Hallucinations in Large Vision-Language Models
Yuying Shang, Xinyi Zeng, Yutao Zhu +6
Hallucinations in large vision-language models (LVLMs) are a significant challenge, i.e., generating objects that are not presented in the visual input, which impairs their reliabi…
MultiTrust: A Comprehensive Benchmark Towards Trustworthy Multimodal Large Language Models
Yichi Zhang, Yao Huang, Yitong Sun +10
Despite the superior capabilities of Multimodal Large Language Models (MLLMs) across diverse tasks, they still face significant trustworthiness challenges. Yet, current literature…
AutoBreach: Universal and Adaptive Jailbreaking with Efficient Wordplay-Guided Optimization
Jiawei Chen, Xiao Yang, Zhengwei Fang +4
Despite the widespread application of large language models (LLMs) across various tasks, recent studies indicate that they are susceptible to jailbreak attacks, which can render th…
How Robust is Google's Bard to Adversarial Image Attacks?
Yinpeng Dong, Huanran Chen, Jiawei Chen +6
Multimodal Large Language Models (MLLMs) that integrate text and other modalities (especially vision) have achieved unprecedented performance in various multimodal tasks. However,…