Efficient Convolution Neural Networks for Object Tracking Using Separable Convolution and Filter Pruning. - Yuanhong Mao; Zhanzhuang He; Zhong Ma; Xuehan Tang; Zhuping Wang (IEEE Access, 2019)

A Weight-Based Channel Pruning Algorithm for Depth-Wise Separable Convolution Unit. - Yizhe Fan; Xuehan Tang; Zhong Ma (ACAI, 2021)

Characterizing and Understanding End-to-End Multi-Modal Neural Networks on GPUs. - Xiaofeng Hou; Cheng Xu; Jiacheng Liu 001; Xuehan Tang; Lingyu Sun; Chao Li 009; Kwang-Ting Cheng (IEEE Comput. Archit. Lett., 2022)

Analyzing the Hardware-Software Implications of Multi-modal DNN Workloads using MMBench. - Xiaofeng Hou; Cheng Xu; Jiacheng Liu 001; Xuehan Tang; Linyu Sun; Chao Li 009; Kwang-Ting Cheng (CoRR, 2022)

MMExit: Enabling Fast and Efficient Multi-modal DNN Inference with Adaptive Network Exits. - Xiaofeng Hou; Jiacheng Liu 001; Xuehan Tang; Chao Li 009; Kwang-Ting Cheng; Li Li 012; Minyi Guo (Euro-Par, 2023)

Architecting Efficient Multi-modal AIoT Systems. - Xiaofeng Hou; Jiacheng Liu 001; Xuehan Tang; Chao Li 009; Jia Chen; Luhong Liang; Kwang-Ting Cheng; Minyi Guo (ISCA, 2023)

WASP: Efficient Power Management Enabling Workload-Aware, Self-Powered AIoT Devices. - Xiaofeng Hou; Xuehan Tang; Jiacheng Liu 001; Chao Li 009; Luhong Liang; Kwang-Ting Cheng (IEEE Trans. Parallel Distributed Syst., 2024)

Improving Efficiency in Multi-Modal Autonomous Embedded Systems Through Adaptive Gating. - Xiaofeng Hou; Cheng Xu; Chao Li 009; Jiacheng Liu 001; Xuehan Tang; Kwang-Ting Cheng; Minyi Guo (IEEE Trans. Computers, 2025)