To enhance the reasoning capabilities of Large Language Models, particularly for complex problems, researchers are developing advanced structures to represent the reasoning process. These structures, such as tree-based and graph-based representations, provide a more organized and compact way to map out reasoning paths. By using these structured representations, LLMs can more effectively explore a wider range of decision-making paths, which is analogous to the deliberate and analytical System 2 thinking in humans.