3 papers
cs.LG2026
Pareto-guided Pipeline for Distilling Featherweight AI Agents in Mobile MOBA Games
Xionghui Yang, Bozhou Chen, Yunlong Lu +8
Recent advances in game AI have demonstrated the feasibility of training agents that surpass top-tier human professionals in complex environments such as Honor of Kings (HoK), a le…
cs.AI2025★ 1 cited
From Capabilities to Performance: Evaluating Key Functional Properties of LLM Architectures in Penetration Testing
Lanxiao Huang, Daksh Dave, Tyler Cody +2
Large language models (LLMs) are increasingly used to automate or augment penetration testing, but their effectiveness and reliability across attack phases remain unclear. We prese…
cs.AI2024
RL-LLM-DT: An Automatic Decision Tree Generation Method Based on RL Evaluation and LLM Enhancement
Junjie Lin, Jian Zhao, Lin Liu +6
Traditionally, AI development for two-player zero-sum games has relied on two primary techniques: decision trees and reinforcement learning (RL). A common approach involves using a…