Concise monthly summary for 2025-01 focusing on key accomplishments, major feature delivered and business value. The primary deliverable this month was improving interoperability for oneDNN across frameworks through dilation formula clarification and documentation updates. This work reduces ambiguity for users integrating oneDNN with PyTorch and TensorFlow and lays groundwork for more robust cross-framework usage. A documentation note was added explaining the dilation computation formula and its differences from PyTorch and TensorFlow, including an explanatory comment in the pooling example to guide parameter adjustments. No major bugs fixed this month; emphasis was on clarity, maintainability, and cross-framework compatibility.