Metacognitive Prompting Improves Understanding in Large Language Models

arXiv:2308.05342v4 Announce Type: replace
Abstract: In Large Language Models (LLMs), there have been consistent advancements in task-specific performance, largely influenced by effective prompt design. Recent advancements in prompting have enhanced reasoning in logic-intensive tasks for LLMs, yet the nuanced understanding abilities of these models, crucial for processing and interpreting complex information, remain underexplored. In this study, we introduce Metacognitive Prompting (MP), a strategy inspired by human introspective reasoning processes. Using MP, LLMs undergo a systematic series of structured, self-aware evaluations, …

abstract arxiv consistent cs.ai cs.cl design information language language models large language large language models llms logic performance processing prompt prompting reasoning tasks type understanding