During October 2024, Sungchul Kim focused on improving the stability of training workflows in the openvinotoolkit/training_extensions repository. He addressed configuration-related bugs in MaskDINO and MonoDETR by removing obsolete parameters from AdaptiveTrainScheduling and EarlyStoppingWithWarmup within YAML files, which reduced misconfigurations and runtime errors. His work involved careful configuration management and model training expertise, ensuring that the development branch aligned with updated MaskDINO recipes. By updating the changelog documentation, Sungchul enhanced traceability for downstream users. The depth of his contribution lay in refining the training pipeline, resulting in more reliable and reproducible experiments for future development efforts.