collaborators

5 papers

cs.CR2026

Coward: Collision-based OOD Watermarking for Practical Proactive Federated Backdoor Detection

Wenjie Li, Siying Gu, Yiming Li +4

Backdoor detection is currently the mainstream defense against backdoor attacks in federated learning (FL), where a small number of malicious clients can upload poisoned updates to…

cs.CR2026

Safety at Scale: A Comprehensive Survey of Large Model and Agent Safety

Xingjun Ma, Yifeng Gao, Yixu Wang +45

The rapid advancement of large models, driven by their exceptional abilities in learning and generalization through large-scale pre-training, has reshaped the landscape of Artifici…

cs.CV2026

GameVerse: Can Vision-Language Models Learn from Video-based Reflection?

Kuan Zhang, Dongchen Liu, Qiyue Zhao +5

Human gameplay is a visually grounded interaction loop in which players act, reflect on failures, and watch tutorials to refine strategies. Can Vision-Language Models (VLMs) also l…

cs.CR2025

A Comprehensive Survey in LLM(-Agent) Full Stack Safety: Data, Training and Deployment

Kun Wang, Guibin Zhang, Zhenhong Zhou +100

The remarkable success of Large Language Models (LLMs) has illuminated a promising pathway toward achieving Artificial General Intelligence for both academic and industrial communi…

cs.RO2025

Unraveling the Effects of Synthetic Data on End-to-End Autonomous Driving

Junhao Ge, Zuhong Liu, Longteng Fan +5

End-to-end (E2E) autonomous driving (AD) models require diverse, high-quality data to perform well across various driving scenarios. However, collecting large-scale real-world data…