Equipping VLM agents with world modeling capabilities has shown strong potential for complex reasoning and long-horizon planning, while reducing the dependence of policy learning on costly real-world interactions. Existing methods mainly rely on prospective simulation to predict the consequences of candidate actions. H...
Yong-Jiang Liu, Jiewei Zhang, Hao-Yue Zhang et al.· 0 citations
Large language model agents have demonstrated promising capabilities in cybersecurity tasks, yet their ability to reconstruct complete Advanced Persistent Threat attack campaigns from complex security logs remains largely unexplored. Existing cybersecurity benchmarks for agents mainly focus on vulnerability discovery,...
Qi Chen, Fu-Shuo Huo, Hang-Li Shen et al.· 0 citations
A novel method named IED is proposed, which leverages the information gain to construct the vector of which each dimension represents the information entropy of each word, and then adopts a classifier to conduct the detection.
Xiao-Quan Yi, Hao-Zhao Wang, Jing-Cai Guo· Proceedings of the Thirty-Fi...· 0 citations
This work proposes OPTD, On-Policy Transition Distillation with consistency-guided adaptive compression, which consistently improves the quality--efficiency trade-off and attains the strongest overall quality-constrained AUP among the evaluated few-step baselines.
Xiaocheng Lu, Hualei Zhang, Shuhan Guo et al.· 0 citations
We use cookies to run the site and, with your consent, for analytics and to show ads.
See our Cookie Policy.