May 14, 2024, 4:49 a.m. | Shuo Yin, Weihao You, Zhilong Ji, Guoqiang Zhong, Jinfeng Bai

cs.CL updates on

arXiv:2405.07551v1 Announce Type: new
Abstract: The tool-use Large Language Models (LLMs) that integrate with external Python interpreters have significantly enhanced mathematical reasoning capabilities for open-source LLMs, while tool-free methods chose another track: augmenting math reasoning data. However, a great method to integrate the above two research paths and combine their advantages remains to be explored. In this work, we firstly include new math questions via multi-perspective data augmenting methods and then synthesize code-nested solutions to them. The open LLMs (i.e., …

abstract arxiv augmentation capabilities code data free however interpreters language language models large language large language models llms math mathematical reasoning perspective python reasoning research tool type while

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