During February 2026, Qneroir enhanced convolution operations in the FlagOpen/FlagGems repository, focusing on improving precision, stability, and performance for low-precision inputs. By enabling FP32 computation pathways within Python-based deep learning code, Qneroir addressed numerical overflow issues and increased the reliability of convolutional layers in production environments. The work leveraged machine learning and performance optimization techniques to ensure that low-precision data could be processed with greater numerical safety and efficiency. Although the contribution was limited to a single feature over one month, the targeted engineering demonstrated a solid understanding of deep learning operations and practical production requirements for model inference.