R${}^3$ Prompting: Review, Rephrase And Resolve For Chain-of-thought Reasoning In Large Language Models Under Noisy Context

Abstract

With the help of Chain-of-Thought (CoT) prompting, Large Language Models (LLMs) have achieved remarkable performance on various reasoning tasks. However, most of them have been evaluated under noise-free context and the dilemma for LLMs to produce inaccurate results under the noisy context has not been fully investigated. Existing studies utilize trigger sentences to encourage LLMs to concentrate