MUSTARD: Mastering Uniform Synthesis of Theorem and Proof Data

arXiv:2402.08957v1 Announce Type: cross
Abstract: Recent large language models (LLMs) have witnessed significant advancement in various tasks, including mathematical reasoning and theorem proving. As these two tasks require strict and formal multi-step inference, they are appealing domains for exploring the reasoning ability of LLMs but still face important challenges. Previous studies such as Chain-of-Thought (CoT) have revealed the effectiveness of intermediate steps guidance. However, such step-wise annotation requires heavy labor, leading to insufficient training steps for current benchmarks. To fill …

arxiv cs.ai cs.cl cs.fl cs.lg cs.pl data synthesis theorem type uniform