L3E-HD: A Framework Enabling Efficient Ensemble in High-Dimensional Space for Language Tasks. - Fangxin Liu; Haomin Li 002; Xiaokang Yang 001; Li Jiang 002 (SIGIR, 2022)

HyperAttack: An Efficient Attack Framework for HyperDimensional Computing. - Fangxin Liu; Haomin Li 002; Yongbiao Chen; Tao Yang 031; Li Jiang 002 (DAC, 2023)

HyperNode: An Efficient Node Classification Framework Using HyperDimensional Computing. - Haomin Li 002; Fangxin Liu; Yichi Chen; Li Jiang 002 (ICCAD, 2023)

TSTC: Enabling Efficient Training via Structured Sparse Tensor Compilation. - Shiyuan Huang; Fangxin Liu; Tian Li; Zongwu Wang; Haomin Li 002; Li Jiang 002 (ASPDAC, 2024)

HyperFeel: An Efficient Federated Learning Framework Using Hyperdimensional Computing. - Haomin Li 002; Fangxin Liu; Yichi Chen; Li Jiang 002 (ASPDAC, 2024)

PAAP-HD: PIM-Assisted Approximation for Efficient Hyper-Dimensional Computing. - Fangxin Liu; Haomin Li 002; Ning Yang; Yichi Chen; Zongwu Wang; Tao Yang 031; Li Jiang 002 (ASPDAC, 2024)

TEAS: Exploiting Spiking Activity for Temporal-wise Adaptive Spiking Neural Networks. - Fangxin Liu; Haomin Li 002; Ning Yang; Zongwu Wang; Tao Yang 031; Li Jiang 002 (ASPDAC, 2024)

INSPIRE: Accelerating Deep Neural Networks via Hardware-friendly Index-Pair Encoding. - Fangxin Liu; Ning Yang; Zhiyan Song; Zongwu Wang; Haomin Li 002; Shiyuan Huang; Zhuoran Song; Songwen Pei; Li Jiang 002 (DAC, 2024)

DEFA: Efficient Deformable Attention Acceleration via Pruning-Assisted Grid-Sampling and Multi-Scale Parallel Processing. - Yansong Xu; Dongxu Lyu; Zhenyu Li; Yuzhou Chen; Zilong Wang; Gang Wang 063; Zhican Wang; Haomin Li 002; Guanghui He (DAC, 2024)

EOS: An Energy-Oriented Attack Framework for Spiking Neural Networks. - Ning Yang; Fangxin Liu; Zongwu Wang; Haomin Li 002; Zhuoran Song; Songwen Pei; Li Jiang 002 (DAC, 2024)

SPARK: Scalable and Precision-Aware Acceleration of Neural Networks via Efficient Encoding. - Fangxin Liu; Ning Yang; Haomin Li 002; Zongwu Wang; Zhuoran Song; Songwen Pei; Li Jiang 002 (HPCA, 2024)

COMPASS: SRAM-Based Computing-in-Memory SNN Accelerator with Adaptive Spike Speculation. - Zongwu Wang; Fangxin Liu; Ning Yang; Shiyuan Huang; Haomin Li 002; Li Jiang 002 (MICRO, 2024)

NeuronQuant: Accurate and Efficient Post-Training Quantization for Spiking Neural Networks. - Haomin Li 002; Fangxin Liu; Zewen Sun; Zongwu Wang; Shiyuan Huang; Ning Yang; Li Jiang 002 (ASP-DAC, 2025)

TAIL: Exploiting Temporal Asynchronous Execution for Efficient Spiking Neural Networks with Inter-Layer Parallelism. - Haomin Li 002; Fangxin Liu; Zongwu Wang; Dongxu Lyu; Shiyuan Huang; Ning Yang; Qi Sun; Zhuoran Song; Li Jiang 002 (DATE, 2025)

HyperDyn: Dynamic Dimensional Masking for Efficient Hyper-Dimensional Computing. - Fangxin Liu; Haomin Li 002; Zongwu Wang; Dongxu Lyu; Li Jiang 002 (DATE, 2025)

CROSS: Compiler-Driven Optimization of Sparse DNNs Using Sparse/Dense Computation Kernels. - Fangxin Liu; Shiyuan Huang; Ning Yang; Zongwu Wang; Haomin Li 002; Li Jiang 002 (HPCA, 2025)

FATE: Boosting the Performance of Hyper-Dimensional Computing Intelligence with Flexible Numerical DAta TypE. - Haomin Li 002; Fangxin Liu; Yichi Chen; Zongwu Wang; Shiyuan Huang; Ning Yang; Dongxu Lyu; Li Jiang 002 (ISCA, 2025)

STCO: Enhancing Training Efficiency via Structured Sparse Tensor Compilation Optimization. - Shiyuan Huang; Fangxin Liu; Tian Li; Zongwu Wang; Ning Yang; Haomin Li 002; Li Jiang 002 (ACM Trans. Design Autom. Electr. Syst., 2025)

ALLMod: Exploring Area-Efficiency of LUT-based Large Number Modular Reduction via Hybrid Workloads. - Fangxin Liu; Haomin Li 002; Zongwu Wang; Bo Zhang; Mingzhe Zhang; Shoumeng Yan; Li Jiang 002; Haibing Guan (CoRR, 2025)

ASDR: Exploiting Adaptive Sampling and Data Reuse for CIM-based Instant Neural Rendering. - Fangxin Liu; Haomin Li 002; Bowen Zhu; Zongwu Wang; Zhuoran Song; Habing Guan; Li Jiang 002 (CoRR, 2025)