Merge pull request #189 from BlackGlory/patch-1

fix typo

pages/techniques/tot.en.mdx

@@ -8,7 +8,7 @@ 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.
 
-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.
+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.
 
 The ToT framework is illustrated below:
 
@@ -25,4 +25,4 @@ Image Source: [Yao et el. (2023)](https://arxiv.org/abs/2305.10601)
 From the results reported in the figure below, ToT substantially outperforms the other prompting methods:
 
 <Screenshot src={TOT2} alt="TOT2" />
-Image Source: [Yao et el. (2023)](https://arxiv.org/abs/2305.10601) 
+Image Source: [Yao et el. (2023)](https://arxiv.org/abs/2305.10601)