36 citations · 91 across the 8 of their papers we have counts for
5 papers · 1 filter
JailbreakSkill: Scaling Automated Red-Teaming with Reusable and Ever-Evolving Skills
Xiaoyu Wen, Jiajia Li, Zhida He +11
Automated red-teaming has produced a growing collection of attack strategies, yet they typically remain scattered across prompts and workflows, making them difficult to systematica…
Not All Turns Matter: Credit Assignment for Multi-Turn Jailbreaking
Zhida He, Xiaoyu Wen, Han Qi +7
Deploying LLMs in multi-turn dialogues facilitates jailbreak attacks that distribute harmful intent across seemingly benign turns. Recent training-based multi-turn jailbreak method…
SAJA: A State-Action Joint Attack Framework on Multi-Agent Deep Reinforcement Learning
Weiqi Guo, Guanjun Liu, Ziyuan Zhou
Multi-Agent Deep Reinforcement Learning (MADRL) has shown potential for cooperative and competitive tasks such as autonomous driving and strategic gaming. However, models trained b…
Multi-Agent Reinforcement Learning: Methods, Applications, Visionary Prospects, and Challenges
Ziyuan Zhou, Guanjun Liu, Ying Tang
Multi-agent reinforcement learning (MARL) is a widely used Artificial Intelligence (AI) technique. However, current studies and applications need to address its scalability, non-st…
Partially Observable Mean Field Multi-Agent Reinforcement Learning Based on Graph-Attention
Min Yang, Guanjun Liu, Ziyuan Zhou
Traditional multi-agent reinforcement learning algorithms are difficultly applied in a large-scale multi-agent environment. The introduction of mean field theory has enhanced the s…