What is tree-of-thoughts?

Tree-of-thoughts — this is a method used in large language models (LLMs) to improve the quality of answer generation by structuring the thinking process as a tree.

Instead of a linear sequential inference, the model generates several reasoning options at each step, forming a tree of possible thought paths. This allows:

• Exploring different approaches to solving the problem.
• Selecting the most logical and relevant branches.
• Enhancing the model's ability for complex reasoning and planning.

Example: when solving a problem, the model first generates several hypotheses, then develops further reasoning for each, discarding less promising ones and focusing on the best options.

This increases the quality and justification of answers compared to simple sequential inference.