Boosting of Thoughts: Trial-and-Error Problem Solving with Large
Language Models
Boosting of Thoughts: Trial-and-Error Problem Solving with Large
Language Models
The reasoning performance of Large Language Models (LLMs) on a wide range of problems critically relies on chain-of-thought prompting, which involves providing a few chain of thought demonstrations as exemplars in prompts. Recent work, e.g., Tree of Thoughts, has pointed out the importance of exploration and self-evaluation in reasoning step …