AI RESEARCH
LoReC: Rethinking Large Language Models for Graph Data Analysis
arXiv CS.LG
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ArXi:2604.17897v1 Announce Type: new The advent of Large Language Models (LLMs) has fundamentally reshaped the way we interact with graphs, giving rise to a new paradigm called GraphLLM. As revealed in recent studies, graph learning can benefit from LLMs. However, we observe limited benefits when we directly utilize LLMs to make predictions for graph-related tasks within GraphLLM paradigm, which even yields suboptimal results compared to conventional GNN-based approaches.