most citedImproving Network Threat Detection by Knowledge Graph, Large Language Model, and Imbalanced Learning

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cs.LG2026

Deep Dense Exploration for LLM Reinforcement Learning via Pivot-Driven Resampling

Yiran Guo, Zhongjian Qiao, Yingqi Xie +5

Effective exploration is a key challenge in reinforcement learning for large language models: discovering high-quality trajectories within a limited sampling budget from the vast n…

cs.LG2025★ 1 cited

Improving Network Threat Detection by Knowledge Graph, Large Language Model, and Imbalanced Learning

Lili Zhang, Quanyan Zhu, Herman Ray +1

Network threat detection has been challenging due to the complexities of attack activities and the limitation of historical threat data to learn from. To help enhance the existing…