During July 2025, Hetul Vagadia focused on improving the reliability of the automated evaluation pipeline for the mlcommons/inference repository. He addressed a parsing issue in the submission checker by correcting a regular expression used to extract ROUGELSUM metric scores from submission results. This targeted, single-line Python fix enhanced the accuracy of benchmark data and reduced the risk of future regressions. Hetul’s work emphasized data integrity and trustworthy feedback in CI/CD workflows, leveraging Python scripting and regular expressions. While no new features were released, his contribution ensured more dependable evaluation results and streamlined the validation process for benchmark submissions.