An algorithm can help guide LLM reasoning to generate correct answers more often. It uses a method similar to Monte Carlo Tree Search to improve outcomes.
By sampling different reasoning steps and keeping track of which ones lead to correct answers, we can better inform the LLMs on how to approach problems.
Having a feedback model to suggest better reasoning steps can enhance the overall performance of LLMs, making them more effective in generating accurate answers.