Kwangjin Ko enhanced the multi-round QA data preprocessing pipeline for the LMCache/LMCache repository, focusing on improving reliability and usability. He implemented data integrity assertions and introduced a dry-run validation option, allowing users to verify data quality before full processing. By enabling model specification for tokenization and filtering out invalid conversation types, he addressed common data inconsistencies. The addition of tqdm-based progress visualization provided real-time feedback during preprocessing. Working primarily in Python, Kwangjin applied skills in data preprocessing, scripting, and command-line interface development. His contributions reflect a thoughtful approach to robust pipeline engineering within a focused, one-month development period.