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

1 citations · 1 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CR2026

Moirae: A Multimodal Agent Collaborative Framework for Dynamic Android Malware Detection

Xueying Zeng, Youquan Xian, Yanze Li +9

The Android ecosystem faces persistent and rapidly evolving malware threats. Existing machine learning detectors are vulnerable to concept drift because they rely on implementation…

cs.CR2026

Safety in Embodied AI: A Survey of Risks, Attacks, and Defenses

Xiao Li, Xiang Zheng, Yifeng Gao +35

Embodied Artificial Intelligence (Embodied AI) integrates perception, cognition, planning, and interaction into agents that operate in open-world, safety-critical environments. As…

cs.CR2026

MARD: A Multi-Agent Framework for Robust Android Malware Detection

Xueying Zeng, Youquan Xian, Sihao Liu +4

With the rapid evolution of Android applications, traditional machine learning-based detection models suffer from concept drift. Additionally, they are constrained by shallow featu…

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.CR2025★ 1 cited

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…