Xavier Wang enhanced CPU embedding lookup functionality in both the Intel-tensorflow/tensorflow and ROCm/tensorflow-upstream repositories by enabling input features to be a subset of the feature configuration keys. He implemented robust input validation to ensure all input keys exist within the configuration, raising errors for mismatches, and adjusted return structures to align with input formats. These updates, developed in Python with a focus on backend development and CPU optimization, included comprehensive test coverage to verify correctness. By establishing cross-repository consistency, Xavier improved serving-time flexibility, reduced misconfiguration risk, and contributed to the maintainability and reliability of TensorFlow’s machine learning workflows.