Paper Explained: Tree of Thoughts — Deliberate Problem Solving with Large Language Models
Note: Generative AI services are used as assistants in this blog post!
This post is a summary of the paper Tree of Thoughts: Deliberate Problem Solving with Large Language Models.
Introduction
There’s been a lot of progress with language models recently. They’re doing a great job with many tasks. But, they’re kind of stuck in a pattern where they make decisions one step at a time, just moving along from start to finish. This isn’t the best when they need to think forward, go back to adjust something, or when the first few decisions are really important.
Now, there’s a new solution called “Tree of Thoughts” or ToT. It’s an improvement on the typical method used for giving prompts to language models, which is called the “Chain of Thought.” The ToT approach lets language models look at larger pieces of text, known as “thoughts.” This means that these models can take their time, consider different options, follow different paths of reasoning, and even evaluate their own decisions to determine what to do next. They can also plan for the future or…
