LLM knowledge, measured by self-reported true/false checks on knowledge-graph triplets, shows homophily and degree correlations that a graph neural network exploits to select more effective fine-tuning data.
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A Graph Perspective to Probe Structural Patterns of Knowledge in Large Language Models
LLM knowledge, measured by self-reported true/false checks on knowledge-graph triplets, shows homophily and degree correlations that a graph neural network exploits to select more effective fine-tuning data.