In this episode we discuss Tree of Thoughts: Deliberate Problem Solving with Large Language Models
by Shunyu Yao, Dian Yu, Jeffrey Zhao, Izhak Shafran, Thomas L. Griffiths, Yuan Cao, Karthik Narasimhan. The authors of this paper introduce a framework called "Tree of Thoughts" (ToT) to enhance language model inference. The ToT framework allows language models to make deliberate decisions by considering multiple reasoning paths and self-evaluating choices. The authors demonstrate the effectiveness of ToT on three tasks, showing significant improvement in problem-solving abilities compared to traditional prompting methods.
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