Review
Graph4LLM: A Systematic Survey of Graph-Enhanced Large Language Models
Xinyan Zhu, Cheng Yang, Qiuyue Wang et al.
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3 papers indexed here
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Preprint
Aug 2026
GABench: A Comprehensive Benchmark for Evaluating LLM Agents on Graph Analysis Tasks
GABench is introduced, a comprehensive benchmark for agentic graph analysis that covers four graph analysis task categories: graph retrieval, graph theory, graph machine learning, and graph open-ended question answering and provides practical insights into the development and evaluation of LLM agents for graph analysis.
Jiarui Tan, Zhongjian Zhang, YaBo Guo et al.
· 0 citations
Preprint
Jul 2026
HiSkill: Empowering LLM Agents with Hierarchical Skill Graphs
Experiments show that HiSkill outperforms state-of-the-art baselines while reducing inference token consumption, demonstrating the effectiveness of bridging high-level skills and executable action grounding through a hierarchical skill graph.
Yu Hao, Jinxuan Cai, Qi Zhang et al.
· 0 citations