Graph Neural Architecture Search with GPT-4

Understand

Graph Neural Architecture Search (GNAS) has shown promising results in finding the best graph neural network architecture on a given graph dataset.

• However, existing GNAS methods still require intensive human labor and rich domain knowledge when designing the search space and search strategy.
• To this end, we integrate Large Language Models (LLMs) into GNAS and present a new GNAS model based on LLMs (GNAS-LLM for short).
• The basic idea of GNAS-LLM is to design a new class of GNAS prompts for LLMs to guide LLMs towards understanding the generative task of graph neural architectures.