Self-Polish: Enhance Reasoning in Large Language Models via Problem Refinement

arXiv:2305.14497v2 Announce Type: replace
Abstract: To enhance the multi-step reasoning capabilities of large language models, researchers have extensively explored prompting methods, notably the Chain-of-Thought (CoT) method which explicitly elicits human-like rationales. However, they have inadvertently overlooked the potential of enhancing model reasoning performance by formulating higher-quality problems. In this work, we start from the problem side and propose Self-Polish (SP), a novel method that facilitates the model's reasoning by guiding it to progressively refine the given problems to be more …

arxiv cs.ai cs.cl language language models large language large language models reasoning type via