Towards Effective Process Supervision in Mathematical Reasoning

Qwen · 1 year ago

Researchers released Qwen2.5-Math-PRM, a process reward model designed to identify errors in intermediate steps of mathematical reasoning by large language models, along with ProcessBench, a benchmark containing 3,400 test cases for evaluating error detection capabilities. The Qwen2.5-Math-PRM-7B model achieves an average improvement of 1.4% over majority voting baselines across seven mathematical benchmarks and outperforms GPT-4o on ProcessBench error identification tasks. This enables better scalable oversight of LLM reasoning processes and provides benchmarks for future research in process supervision for mathematical problem-solving.