Towards Generalizable and Faithful Logic Reasoning over Natural Language via Resolution Refutation

arXiv:2404.01677v1 Announce Type: cross
Abstract: Large language models (LLMs) have achieved significant performance in various natural language reasoning tasks. However, they still struggle with performing first-order logic reasoning over formal logical theories expressed in natural language. This is because the previous LLMs-based reasoning systems have the theoretical incompleteness issue. As a result, it can only address a limited set of simple reasoning problems, which significantly decreases their generalization ability. To address this issue, we propose a novel framework, named Generalizable …

abstract arxiv cs.ai cs.cl however language language models large language large language models llms logic natural natural language performance reasoning resolution struggle systems tasks type via