Talk like a graph: Encoding graphs for large language models

The post discusses the encoding of graphs for large language models (LLMs) and how it impacts LLM performance on graph tasks. It introduces a benchmark called GraphQA that evaluates LLMs on graph-specific problems. The study found that the encoding method, task type, and graph structure all influence LLM performance. The right encoding techniques can significantly improve LLM accuracy on graph problems.