During August 2025, Xiaochuan Luo focused on improving model training stability in the liguodongiot/transformers repository. He addressed a bug in the Qwen2_5_VLForConditionalGeneration model by correcting how vocab_size was handled in the loss computation, ensuring the correct configuration value was used. This targeted fix, implemented in Python and leveraging deep learning and model training expertise, reduced training noise and improved the accuracy of loss metrics. Xiaochuan also propagated similar adjustments to related models, promoting codebase consistency and reducing the risk of miscalculated losses. His work enhanced the reliability of evaluation metrics across the machine learning pipeline.