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What happens when you combine the Chain of Thought (CoT) reasoning capabilities of LLMs with a heuristic-guided tree search algorithm? In the Tree of Thoughts (ToT) paper, the authors (Yao et al.) have coupled GPT-4 with tree search algorithms to attack a few tasks on which left-to-right CoT struggles. And the results are impressive. For example, on the "Game of 24" task, while GPT-4 with CoT prompting only managed to solve 4% of tasks, ToT achieved a success rate of 74%.
I've written a blog post that makes the ToT paper easy to understand and implement by taking you through all the details in a step-by-step manner: https://huggingface.co/blog/sadhaklal/tree-of-thoughts
If you are interested in the topics of algorithmic AI, tree search, reasoning, planning, or "System 2" thinking, then you may find this blog post useful.
I've written a blog post that makes the ToT paper easy to understand and implement by taking you through all the details in a step-by-step manner: https://huggingface.co/blog/sadhaklal/tree-of-thoughts
If you are interested in the topics of algorithmic AI, tree search, reasoning, planning, or "System 2" thinking, then you may find this blog post useful.
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