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Jieyi Long (THETA Network) 2023-06-09 03:21:07 -07:00 committed by GitHub
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@ -6,7 +6,7 @@ import TOT from '../../img/TOT.png'
import TOT2 from '../../img/TOT2.png'
import TOT3 from '../../img/TOT3.png'
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.
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) and [Long (2023)](https://arxiv.org/abs/2305.08291) 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.
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.
@ -27,4 +27,4 @@ From the results reported in the figure below, ToT substantially outperforms the
<Screenshot src={TOT3} alt="TOT3" />
Image Source: [Yao et el. (2023)](https://arxiv.org/abs/2305.10601)
Code available [here](https://github.com/princeton-nlp/tree-of-thought-llm)
Code available [here](https://github.com/princeton-nlp/tree-of-thought-llm) and [here](https://github.com/jieyilong/tree-of-thought-puzzle-solver)