10 citations · 11 across the 16 of their papers we have counts for
9 papers · 1 filter
VibeGame: Prompt-to-Game Development with AI-Native Engine and Self-Evolving Adversarial Agent Team
Wenbo Hu, Ken Li, Jiazhe Wei +13
Large language model agents have enabled software development through natural-language interaction, but extending this paradigm to end-to-end game development remains challenging.…
MME-Safety: A Fine-grained Benchmark for Safety Evaluation of MLLMs
Yilian Shi, Yueming Lyu, Haoxiang Tan +5
While Multimodal Large Language Models (MLLMs) show remarkable advancements, their cross-modal capabilities introduce complex vulnerabilities that easily bypass unimodal filters. E…
PRMU: A Corpus-Free Benchmark for Person-Centric Knowledge Unlearning in Multimodal Large Language Models
Huafeng Chen, Yueming Lyu, Ziyuan Chen +4
Multimodal large language models (MLLMs) have demonstrated remarkable capabilities in storing and recalling rich person-related knowledge, raising increasing concerns about reliabl…
Is There Really a Camouflaged Object? Towards Realistic Camouflaged Object Detection
Huafeng Chen, Yueming Lyu, Chenyang Si +3
Camouflaged object detection (COD) aims to segment objects that are visually concealed in their surroundings and has attracted increasing attention in recent years. However, most e…
Hierarchical Anti-Aesthetics: Protecting Facial Privacy against Customized Diffusion Models
Songping Wang, Yueming Lyu, Shiqi Liu +5
The rise of customized diffusion models has fueled a boom in personalized visual content creation, but it also introduces serious risks of malicious misuse, thereby posing threats…
AgentCanary: A Security Evaluation Framework for Autonomous AI Agents in Real Executable Environments
Peiyang Li, Songping Wang, Yi Huang +9
Autonomous AI agents have driven the transition from conversation to task execution, shifting security failures from textual deception to system compromise. Although security evalu…
Confundo: Learning to Generate Robust Poison for Practical RAG Systems
Haoyang Hu, Zhejun Jiang, Yueming Lyu +3
Retrieval-augmented generation (RAG) is increasingly deployed in real-world applications, where its reference-grounded design makes outputs appear trustworthy. This trust has spurr…
Exposing and Defending the Achilles' Heel of Video Mixture-of-Experts
Songping Wang, Qinglong Liu, Yueming Lyu +3
Mixture-of-Experts (MoE) has demonstrated strong performance in video understanding tasks, yet its adversarial robustness remains underexplored. Existing attack methods often treat…
StableWorld: Towards Stable and Consistent Long Interactive Video Generation
Ying Yang, Zhengyao Lv, Yujia Zeng +9
In this paper, we explore the overlooked challenge of stability and temporal consistency in interactive video generation, which synthesizes dynamic and controllable video worlds th…