[R] MathScale: Scaling Instruction Tuning for Mathematical Reasoning

**Paper**: [https://arxiv.org/abs/2403.02884](https://arxiv.org/abs/2403.02884)

**Abstract**:

>Large language models (LLMs) have demonstrated remarkable capabilities in problem-solving. However, their proficiency in solving mathematical problems remains inadequate. We propose **MathScale**, a simple and scalable method to create high-quality mathematical reasoning data using frontier LLMs (e.g., GPT-3.5). Inspired by the cognitive mechanism in human mathematical learning, it first extracts topics and knowledge points from seed math questions and then build a concept graph, which is subsequently used to generate new math questions. MathScale exhibits effective scalability …

abstract capabilities cognitive data gpt gpt-3 gpt-3.5 however human knowledge language language models large language large language models llms machinelearning math mathematical reasoning problem-solving quality questions reasoning scalable seed simple topics