<ul><li>The Tree-of-Thoughts (ToT) methodology allows language models to make decisions by exploring different reasoning paths and evaluating their progress.</li><li>ToT is inspired by a problem-solving concept from the 1950s and uses a tree structure to represent different thoughts and potential solutions.</li><li>ToT involves thought decomposition, thought generation, state evaluation, and search algorithms to explore the problem space.</li><li>Experiments on challenging tasks showed that ToT outperformed standard prompting and chain-of-thought prompting approaches.</li></ul>

Paper Insights: Tree-of -Thoughts: Deliberate Problem Solving with Large Language Models

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