BoT: Enhanced Thinking: Solving Trial and Error Problems with Large Language Models
Abstract The reasoning performance of Large Language Models (LLMs) on a wide range of problems relies heavily on chained-thinking cues, which involves providing some chained-thinking demonstrations as examples in the cues. Recent research, e.g., thinking trees, has pointed to exploration and self-assessment of reasoning steps in complex problem solving ...