A recent study suggests that visual graph structures can significantly enhance the reasoning capabilities of large language models (LLMs) by organizing thought processes, rather than just serving as external knowledge sources. The findings indicate that using graphs as internal reasoning aids improves efficiency and answer quality, even without direct answer hints, highlighting their potential in LLM development.