A Closer Look at the Self-Verification Abilities of Large Language Models in Logical Reasoning

arXiv:2311.07954v2 Announce Type: replace-cross
Abstract: Logical reasoning has been an ongoing pursuit in the field of AI. Despite significant advancements made by large language models (LLMs), they still struggle with complex logical reasoning problems. To enhance reasoning performance, one promising direction is scalable oversight, which requires LLMs to identify their own errors and then improve by themselves. Various self-verification methods have been proposed in pursuit of this goal. Nevertheless, whether existing models understand their own errors well is still under …

abstract arxiv closer look cs.ai cs.cl language language models large language large language models llms look oversight performance reasoning scalable struggle type verification