From 6802abc065ec299f29d317dfa9cff95cef32b81f Mon Sep 17 00:00:00 2001 From: BlackGlory Date: Tue, 6 Jun 2023 02:18:48 +0800 Subject: [PATCH] fix typo breath-first search => breadth-first search --- pages/techniques/tot.en.mdx | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/pages/techniques/tot.en.mdx b/pages/techniques/tot.en.mdx index 0f8d1b4..8f931d8 100644 --- a/pages/techniques/tot.en.mdx +++ b/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: -Image Source: [Yao et el. (2023)](https://arxiv.org/abs/2305.10601) \ No newline at end of file +Image Source: [Yao et el. (2023)](https://arxiv.org/abs/2305.10601)