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20242026
most citedNavigating the Risks: A Survey of Security, Privacy, and Ethics Threats in LLM-Based Agents

8 citations · 8 across the 4 of their papers we have counts for

collaborators

6 papers

cs.CV2026

Beauty and the Beast: Imperceptible Perturbations Against Diffusion-Based Face Swapping via Directional Attribute Editing

Yilong Huang, Songze Li

Diffusion-based face swapping achieves state-of-the-art performance, yet it also exacerbates the potential harm of malicious face swapping to violate portraiture right or undermine…

cs.CR2025

Responsible Diffusion: A Comprehensive Survey on Safety, Ethics, and Trust in Diffusion Models

Kang Wei, Xin Yuan, Fushuo Huo +5

Diffusion models (DMs) have been investigated in various domains due to their ability to generate high-quality data, thereby attracting significant attention. However, similar to t…

cs.CR2025

FuncPoison: Poisoning Function Library to Hijack Multi-agent Autonomous Driving Systems

Yuzhen Long, Songze Li

Autonomous driving systems increasingly rely on multi-agent architectures powered by large language models (LLMs), where specialized agents collaborate to perceive, reason, and pla…

cs.LG2025

Policy Disruption in Reinforcement Learning:Adversarial Attack with Large Language Models and Critical State Identification

Junyong Jiang, Buwei Tian, Chenxing Xu +2

Reinforcement learning (RL) has achieved remarkable success in fields like robotics and autonomous driving, but adversarial attacks designed to mislead RL systems remain challengin…

cs.CR2025

TooBadRL: Trigger Optimization to Boost Effectiveness of Backdoor Attacks on Deep Reinforcement Learning

Mingxuan Zhang, Oubo Ma, Kang Wei +2

Deep reinforcement learning (DRL) has achieved remarkable success in a wide range of sequential decision-making applications, including robotics, healthcare, smart grids, and finan…

cs.AI20248 cited

Navigating the Risks: A Survey of Security, Privacy, and Ethics Threats in LLM-Based Agents

Yuyou Gan, Yong Yang, Zhe Ma +10

With the continuous development of large language models (LLMs), transformer-based models have made groundbreaking advances in numerous natural language processing (NLP) tasks, lea…