M ath M ixup: Boosting LLM Mathematical Reasoning with Difficulty-Controllable Data Synthesis and Curriculum Learning
Xuchen Li · Jing Chen · Xuzhao Li · Hao Liang · Xiaohuan ZHOU · Taifeng Wang · Wentao Zhang
摘要
In mathematical reasoning tasks, the advancement of Large Language Models (LLMs) relies heavily on high-quality training data with clearly defined and well-graded difficulty levels. However, existing data synthesis methods often suffer from limited diversity and lack precise control over problem...