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https://github.com/dair-ai/Prompt-Engineering-Guide
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fix typo
breath-first search => breadth-first search
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@ -8,7 +8,7 @@ import TOT3 from '../../img/TOT3.png'
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For complex tasks that require exploration or strategic lookahead, traditional or simple prompting techniques fall short. [Yao et el. (2023)](https://arxiv.org/abs/2305.10601) recently proposed Tree of Thoughts (ToT), a framework that generalizes over chain-of-thought prompting and encourages exploration over thoughts that serve as intermediate steps for general problem solving with language models.
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ToT maintains a tree of thoughts, where thoughts represent coherent language sequences that serve as intermediate steps toward solving a problem. This approach enables an LM to self-evaluate the progress intermediate thoughts make towards solving a problem through a deliberate reasoning process. The LM ability to generate and evaluate thoughts is then combined with search algorithms (e.g., breath-first search and depth-first search) to enable systematic exploration of thoughts with lookahead and backtracking.
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ToT maintains a tree of thoughts, where thoughts represent coherent language sequences that serve as intermediate steps toward solving a problem. This approach enables an LM to self-evaluate the progress intermediate thoughts make towards solving a problem through a deliberate reasoning process. The LM ability to generate and evaluate thoughts is then combined with search algorithms (e.g., breadth-first search and depth-first search) to enable systematic exploration of thoughts with lookahead and backtracking.
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The ToT framework is illustrated below:
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@ -25,4 +25,4 @@ Image Source: [Yao et el. (2023)](https://arxiv.org/abs/2305.10601)
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From the results reported in the figure below, ToT substantially outperforms the other prompting methods:
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<Screenshot src={TOT2} alt="TOT2" />
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Image Source: [Yao et el. (2023)](https://arxiv.org/abs/2305.10601)
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Image Source: [Yao et el. (2023)](https://arxiv.org/abs/2305.10601)
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