Genuine advancement of LLM mathematical reasoning and reliability of GSM8K metrics

Determine whether the observed improvements in large language models’ accuracy on the GSM8K benchmark correspond to genuine advances in mathematical reasoning capabilities, and ascertain the reliability of performance metrics reported on GSM8K in reflecting true mathematical reasoning ability.

Background

The GSM8K benchmark is widely used to assess mathematical reasoning at a grade-school level, and reported accuracy for many LLMs has risen substantially. However, GSM8K is a static, popular test set that may suffer from data contamination and lacks controllable variability, potentially inflating or misrepresenting true reasoning gains. The authors introduce GSM-Symbolic to generate diverse, controlled variants, observing notable performance variance and drops when only numerical values or complexity are changed, which raises doubts about whether GSM8K improvements reflect genuine reasoning advances.

This problem centers on validating whether increased GSM8K scores genuinely measure mathematical reasoning rather than pattern matching or overfitting, and on assessing the reliability of GSM8K-reported metrics as faithful indicators of reasoning ability.