Exploring the Potential of Large Language Models in Graph Generation

arXiv:2403.14358v1 Announce Type: new
Abstract: Large language models (LLMs) have achieved great success in many fields, and recent works have studied exploring LLMs for graph discriminative tasks such as node classification. However, the abilities of LLMs for graph generation remain unexplored in the literature. Graph generation requires the LLM to generate graphs with given properties, which has valuable real-world applications such as drug discovery, while tends to be more challenging. In this paper, we propose LLM4GraphGen to explore the ability …

abstract arxiv classification cs.ai cs.lg fields graph however language language models large language large language models literature llm llms node q-bio.bm success tasks type