The study introduces COP as a novel reasoning approach to enhance deductive reasoning with large language models. By organizing information systematically, COP reduces errors and improves inference efficiency. Experimental results demonstrate COP's superiority over existing methods across various deductive benchmarks.
The study focuses on leveraging human problem-solving insights to streamline reasoning processes for large language models. By distilling relevant information and organizing it effectively, COP enhances the deductive reasoning capabilities of these models. The proposed approach significantly outperforms state-of-the-art methods in complex logical reasoning tasks.
Through concept maps and mind map generation, COP simplifies the understanding of complex reasoning contexts, leading to more accurate deductions. The method's effectiveness is evident in its ability to reduce misleading steps and improve overall performance on deductive benchmarks.
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by Shaotian Yan... at arxiv.org 03-04-2024
https://arxiv.org/pdf/2310.03309.pdfDeeper Inquiries