Relations (1)

related 2.00 — strongly supporting 3 facts

Large Language Models and graphs are linked through academic research exploring their integration, specifically in knowledge-graph-based retrieval-augmented generation [1], graph encoding techniques for LLMs [2], and comprehensive surveys on applying LLMs to graph-structured data [3].

Facts (3)

Sources
Empowering GraphRAG with Knowledge Filtering and Integration arxiv.org arXiv 1 fact
referenceMufei Li, Siqi Miao, and Pan Li authored 'Simple is effective: The roles of graphs and large language models in knowledge-graph-based retrieval-augmented generation', published in the International Conference on Learning Representations.
LLM-Powered Knowledge Graphs for Enterprise Intelligence and ... arxiv.org arXiv 1 fact
referenceJin, B., Liu, G., Han, C., Jiang, M., Ji, H., and Han, J. authored the arXiv preprint 'Large language models on graphs: A comprehensive survey' (arXiv:2312.02783) in 2024.
A survey on augmenting knowledge graphs (KGs) with large ... link.springer.com Springer 1 fact
referenceFatemi, Halcrow, and Perozzi authored 'Talk like a graph: encoding graphs for large language models', an arXiv preprint published in 2023 (arXiv:2310.04560).