During November 2025, Zhiqiang Gao focused on improving the accuracy and reliability of the attention backend in the NVIDIA/TensorRT-LLM repository. He addressed a precision issue in the FlashInfer attention mechanism by correcting the key-value (KV) cache handling for split and concat kernels, ensuring alignment with the specified tensor layout. This work involved low-level kernel debugging and careful management of tensor operations using Python and PyTorch, with an emphasis on deep learning and unit testing. By validating the impact on model inference, Zhiqiang contributed to more trustworthy production deployments and reduced precision drift in high-performance inference workloads.