Work-in-Progress: BloCirNN: An Efficient Software/hardware Codesign Approach for Neural Network Accelerators with Block-Circulant Matrix. - Yunji Qin; Lei Gong; Zhendong Zheng; Chao Wang 003 (CODES+ISSS, 2022)

Enhancing Long Sequence Input Processing in FPGA-Based Transformer Accelerators through Attention Fusion. - Yunji Qin; Wenqi Lou; Chao Wang 003; Lei Gong; Xuehai Zhou (ACM Great Lakes Symposium on VLSI, 2024)

MFNAS: Multi-fidelity Exploration in Neural Architecture Search with Stable Zero-Shot Proxy. - Wei Fu; Wenqi Lou; Yunji Qin; Lei Gong; Chao Wang 003; Xuehai Zhou (PRICAI (1), 2024)

FlexBCM: Hybrid Block-Circulant Neural Network and Accelerator Co-Search on FPGAs. - Wenqi Lou; Yunji Qin; Xuan Wang 020; Lei Gong; Chao Wang 003; Xuehai Zhou (IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 2024)

UbiMoE: A Ubiquitous Mixture-of-Experts Vision Transformer Accelerator With Hybrid Computation Pattern on FPGA. - Jiale Dong; Wenqi Lou; Zhendong Zheng; Yunji Qin; Lei Gong; Chao Wang; Xuehai Zhou (ISCAS, 2025)

UbiMoE: A Ubiquitous Mixture-of-Experts Vision Transformer Accelerator With Hybrid Computation Pattern on FPGA. - Jiale Dong; Wenqi Lou; Zhendong Zheng; Yunji Qin; Lei Gong; Chao Wang 003; Xuehai Zhou (CoRR, 2025)