{"ID":2878003,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2508.18824","arxiv_id":"2508.18824","title":"Arrows of Math Reasoning Data Synthesis for Large Language Models: Diversity, Complexity and Correctness","abstract":"Enhancing the mathematical reasoning of large language models (LLMs) demands high-quality training data, yet conventional methods face critical challenges in scalability, cost, and data reliability. To address these limitations, we propose a novel program-assisted synthesis framework that systematically generates a high-quality mathematical corpus with guaranteed diversity, complexity, and correctness. This framework integrates mathematical knowledge systems and domain-specific tools to create executable programs. These programs are then translated into natural language problem-solution pairs and vetted by a bilateral validation mechanism that verifies solution correctness against program outputs and ensures program-problem consistency. We have generated 12.3 million such problem-solving triples. Experiments demonstrate that models fine-tuned on our data significantly improve their inference capabilities, achieving state-of-the-art performance on several benchmark datasets and showcasing the effectiveness of our synthesis approach.","short_abstract":"Enhancing the mathematical reasoning of large language models (LLMs) demands high-quality training data, yet conventional methods face critical challenges in scalability, cost, and data reliability. To address these limitations, we propose a novel program-assisted synthesis framework that systematically generates a hig...","url_abs":"https://arxiv.org/abs/2508.18824","url_pdf":"https://arxiv.org/pdf/2508.18824v1","authors":"[\"Sirui Chen\",\"Changxin Tian\",\"Binbin Hu\",\"Kunlong Chen\",\"Ziqi Liu\",\"Zhiqiang Zhang\",\"Jun Zhou\"]","published":"2025-08-26T09:01:50Z","proceeding":"cs.CL","tasks":"[\"cs.CL\"]","methods":"[\"Large Language Model\",\"Language Model\"]","has_code":false}