Cong Liu developed and delivered a dead dynamic-update-slice elimination optimization pass for XLA in both the Intel-tensorflow/xla and ROCm/tensorflow-upstream repositories. Using C++ and leveraging expertise in HLO transformations and compiler optimization, Cong identified and removed unnecessary dynamic-update-slice instructions that did not impact downstream operations, thereby reducing redundant computations and improving runtime performance. The work ensured cross-repository consistency in optimization strategies, supporting maintainability and runtime gains across platforms. Cong maintained high code quality by providing detailed commit messages and metadata, enabling traceability and auditability. The depth of the implementation reflects a strong understanding of compiler design and performance optimization.