Driven by the rapid development of Large Language Models (LLMs), LLM-based agents
have been developed to handle various real-world applications, including finance …

The safety of decentralized reinforcement learning (RL) is a challenging problem since
malicious agents can share their poisoned policies with benign agents. The paper …

Recently, Text-to-Image (T2I) synthesis technology has made tremendous strides.
Numerous representative T2I models have emerged and achieved promising application …

Recent studies have shown that cooperative multi-agent deep reinforcement learning (c-
MADRL) is under the threat of backdoor attacks. Once a backdoor trigger is observed, it will …

Offline reinforcement learning, which learns solely from datasets without environmental
interaction, has gained attention. This approach, similar to traditional online deep …

针对现有离线**化学**数据投毒攻击方法有效性及隐蔽性不足的问题, 提出一种关键时间步动态
投毒攻击方法, 通过对重要性较高的样本进行动态扰动, 实现高效隐蔽的攻击效果. 具体来说 …

The field of software engineering has witnessed a surge in large language models
specifically tailored to understand and process code, which we call large language models …

End-to-end autonomous driving (AD) systems integrate complex decision-making
processes. Assessing the safety of these systems against potential security threats, including …