A mechanism of topology optimization for underwater acoustic sensor networks based on autonomous underwater vehicles. - Ming He; Fangxin Liu; Zhuang Miao; Huan Zhou; Qiuli Chen (Int. J. Distributed Sens. Networks, 2017)

UAV 3D Mobility Model Oriented to Dynamic and Uncertain Environment. - Na Wang; Nan Di; Fei Dai 008; Fangxin Liu (ICA3PP (3), 2018)

Dynamic Obstacle Avoidance Planning Algorithm for UAV Based on Dubins Path. - Na Wang; Fei Dai 008; Fangxin Liu; Guomin Zhang (ICA3PP (2), 2018)

LHC: A Low-Power Heterogeneous Computing Method on Neural Network Accelerator. - Fangxin Liu; Kunpeng Xie; Cheng Gong; Shusheng Liu; Ye Lu 004; Tao Li 022 (ICPADS, 2019)

ExploreBP: A Simulation Tool for Mobile Browser Energy Optimization. - Jin Zhang 003; Xin Wei; Zhen Liu; Fangxin Liu; Tao Li 022; Tingjuan Lu; Xiaoli Gong (SimuTools, 2019)

Characterizing the I/O Pipeline in the Deployment of CNNs on Commercial Accelerators. - Jiansong Li; Zihan Jiang; Fangxin Liu; Xiao Dong; Guangli Li; Xueying Wang 003; Wei Cao 010; Lei Liu 030; Yanzhi Wang; Tao Li 022; Xiaobing Feng 002 (ISPA/BDCloud/SocialCom/SustainCom, 2020)

AUSN: Approximately Uniform Quantization by Adaptively Superimposing Non-uniform Distribution for Deep Neural Networks. - Fangxin Liu; Wenbo Zhao 005; Yanzhi Wang; Changzhi Dai; Li Jiang 002 (CoRR, 2020)

PIMGCN: A ReRAM-Based PIM Design for Graph Convolutional Network Acceleration. - Tao Yang 031; Dongyue Li; Yibo Han; Yilong Zhao; Fangxin Liu; Xiaoyao Liang; Zhezhi He; Li Jiang 002 (DAC, 2021)

IM3A: Boosting Deep Neural Network Efficiency via In-Memory Addressing-Assisted Acceleration. - Fangxin Liu; Wenbo Zhao 005; Zongwu Wang; Tao Yang 031; Li Jiang 002 (ACM Great Lakes Symposium on VLSI, 2021)

Bit-Transformer: Transforming Bit-level Sparsity into Higher Preformance in ReRAM-based Accelerator. - Fangxin Liu; Wenbo Zhao 005; Zhezhi He; Zongwu Wang; Yilong Zhao; Yongbiao Chen; Li Jiang 002 (ICCAD, 2021)

SME: ReRAM-based Sparse-Multiplication-Engine to Squeeze-Out Bit Sparsity of Neural Network. - Fangxin Liu; Wenbo Zhao 005; Zhezhi He; Zongwu Wang; Yilong Zhao; Tao Yang 031; Jingnai Feng; Xiaoyao Liang; Li Jiang 002 (ICCD, 2021)

Improving Neural Network Efficiency via Post-training Quantization with Adaptive Floating-Point. - Fangxin Liu; Wenbo Zhao 005; Zhezhi He; Yanzhi Wang; Zongwu Wang; Changzhi Dai; Xiaoyao Liang; Li Jiang 002 (ICCV, 2021)

SME: ReRAM-based Sparse-Multiplication-Engine to Squeeze-Out Bit Sparsity of Neural Network. - Fangxin Liu; Wenbo Zhao 005; Yilong Zhao; Zongwu Wang; Tao Yang 031; Zhezhi He; Naifeng Jing; Xiaoyao Liang; Li Jiang 002 (CoRR, 2021)

BISWSRBS: A Winograd-based CNN Accelerator with a Fine-grained Regular Sparsity Pattern and Mixed Precision Quantization. - Tao Yang 031; Zhezhi He; Tengchuan Kou; Qingzheng Li; Qi Han; Haibao Yu; Fangxin Liu; Yun Liang 001; Li Jiang 002 (ACM Trans. Reconfigurable Technol. Syst., 2021)

SpikeConverter: An Efficient Conversion Framework Zipping the Gap between Artificial Neural Networks and Spiking Neural Networks. - Fangxin Liu; Wenbo Zhao 005; Yongbiao Chen; Zongwu Wang; Li Jiang 002 (AAAI, 2022)

HAWIS: Hardware-Aware Automated WIdth Search for Accurate, Energy-Efficient and Robust Binary Neural Network on ReRAM Dot-Product Engine. - Qidong Tang; Zhezhi He; Fangxin Liu; Zongwu Wang; Yiyuan Zhou; Yinghuan Zhang; Li Jiang 002 (ASP-DAC, 2022)

PIM-DH: ReRAM-based processing-in-memory architecture for deep hashing acceleration. - Fangxin Liu; Wenbo Zhao 005; Yongbiao Chen; Zongwu Wang; Zhezhi He; Rui Yang; Qidong Tang; Tao Yang 031; Cheng Zhuo; Li Jiang 002 (DAC, 2022)

EBSP: evolving bit sparsity patterns for hardware-friendly inference of quantized deep neural networks. - Fangxin Liu; Wenbo Zhao 005; Zongwu Wang; Yongbiao Chen; Zhezhi He; Naifeng Jing; Xiaoyao Liang; Li Jiang 002 (DAC, 2022)

SATO: spiking neural network acceleration via temporal-oriented dataflow and architecture. - Fangxin Liu; Wenbo Zhao 005; Zongwu Wang; Yongbiao Chen; Tao Yang 031; Zhezhi He; Xiaokang Yang 001; Li Jiang 002 (DAC, 2022)

Self-Terminating Write of Multi-Level Cell ReRAM for Efficient Neuromorphic Computing. - Zongwu Wang; Zhezhi He; Rui Yang; Shiquan Fan; Jie Lin 004; Fangxin Liu; Yueyang Jia; Chenxi Yuan; Qidong Tang; Li Jiang 002 (DATE, 2022)

DTQAtten: Leveraging Dynamic Token-based Quantization for Efficient Attention Architecture. - Tao Yang 031; Dongyue Li; Zhuoran Song; Yilong Zhao; Fangxin Liu; Zongwu Wang; Zhezhi He; Li Jiang 002 (DATE, 2022)

DynSNN: A Dynamic Approach to Reduce Redundancy in Spiking Neural Networks. - Fangxin Liu; Wenbo Zhao 005; Yongbiao Chen; Zongwu Wang; Fei Dai 008 (ICASSP, 2022)

Randomize and Match: Exploiting Irregular Sparsity for Energy Efficient Processing in SNNs. - Fangxin Liu; Zongwu Wang; Wenbo Zhao 005; Yongbiao Chen; Tao Yang 031; Xiaokang Yang 001; Li Jiang 002 (ICCD, 2022)

Supervised Contrastive Vehicle Quantization for Efficient Vehicle Retrieval. - Yongbiao Chen; Kaicheng Guo; Fangxin Liu; Yusheng Huang; Zhengwei Qi (ICMR, 2022)

TransHash: Transformer-based Hamming Hashing for Efficient Image Retrieval. - Yongbiao Chen; Sheng Zhang; Fangxin Liu; Zhigang Chang; Mang Ye; Zhengwei Qi (ICMR, 2022)

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)

A systematic study on benchmarking AI inference accelerators. - Zihan Jiang; Jiansong Li; Fangxin Liu; Wanling Gao; Lei Wang 004; Chuanxin Lan; Fei Tang; Lei Liu 030; Tao Li 022 (CCF Trans. High Perform. Comput., 2022)

RePAST: A ReRAM-based PIM Accelerator for Second-order Training of DNN. - Yilong Zhao; Li Jiang 002; Mingyu Gao 001; Naifeng Jing; Chengyang Gu; Qidong Tang; Fangxin Liu; Tao Yang 031; Xiaoyao Liang (CoRR, 2022)

IVQ: In-Memory Acceleration of DNN Inference Exploiting Varied Quantization. - Fangxin Liu; Wenbo Zhao 005; Zongwu Wang; Yilong Zhao; Tao Yang 031; Yiran Chen 001; Li Jiang 002 (IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 2022)

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

SIMSnn: A Weight-Agnostic ReRAM-based Search-In-Memory Engine for SNN Acceleration. - Fangxin Liu; Wenbo Zhao 005; Zongwu Wang; Xiaokang Yang 001; Li Jiang 002 (DATE, 2023)

PIMPR: PIM-based Personalized Recommendation with Heterogeneous Memory Hierarchy. - Tao Yang 031; Hui Ma; Yilong Zhao; Fangxin Liu; Zhezhi He; Xiaoli Sun; Li Jiang 002 (DATE, 2023)

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

PSQ: An Automatic Search Framework for Data-Free Quantization on PIM-based Architecture. - Fangxin Liu; Ning Yang; Li Jiang 002 (ICCD, 2023)

SoBS-X: Squeeze-Out Bit Sparsity for ReRAM-Crossbar-Based Neural Network Accelerator. - Fangxin Liu; Zongwu Wang; Yongbiao Chen; Zhezhi He; Tao Yang 031; Xiaoyao Liang; Li Jiang 002 (IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 2023)

PASGCN: An ReRAM-Based PIM Design for GCN With Adaptively Sparsified Graphs. - Tao Yang 031; Dongyue Li; Fei Ma; Zhuoran Song; Yilong Zhao; Jiaxi Zhang 001; Fangxin Liu; Li Jiang 002 (IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 2023)

DTATrans: Leveraging Dynamic Token-Based Quantization With Accuracy Compensation Mechanism for Efficient Transformer Architecture. - Tao Yang 031; Fei Ma; Xiaoling Li; Fangxin Liu; Yilong Zhao; Zhezhi He; Li Jiang 002 (IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 2023)

DVHN: A Deep Hashing Framework for Large-Scale Vehicle Re-Identification. - Yongbiao Chen; Sheng Zhang; Fangxin Liu; Chenggang Wu; Kaicheng Guo; Zhengwei Qi (IEEE Trans. Intell. Transp. Syst., 2023)

A Point Cloud Video Recognition Acceleration Framework Based on Tempo-Spatial Information. - Zhuoran Song; Wanzhen Liu; Tao Yang 031; Fangxin Liu; Naifeng Jing; Xiaoyao Liang (IEEE Trans. Parallel Distributed Syst., 2023)

Performance Analysis of ASTARS-Assisted Uplink Communication Networks. - Fangxin Liu; Yingjie Pei; Xuefei Zhang; Xiaofeng Tao (APCC, 2024)

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)

CMC: Video Transformer Acceleration via CODEC Assisted Matrix Condensing. - Zhuoran Song; Chunyu Qi; Fangxin Liu; Naifeng Jing; Xiaoyao Liang (ASPLOS (2), 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)

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)

Sava: A Spatial- and Value-Aware Accelerator for Point Cloud Transformer. - Xueyuan Liu 001; Zhuoran Song; Xiang Liao; Xing Li; Tao Yang 031; Fangxin Liu; Xiaoyao Liang (DATE, 2024)

RTSA: An RRAM-TCAM based In-Memory-Search Accelerator for Sub-100 µs Collision Detection. - Jiahao Sun; Fangxin Liu; Yijian Zhang; Li Jiang 002; Rui Yang (DATE, 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)

HOLES: Boosting Large Language Models Efficiency with Hardware-Friendly Lossless Encoding. - Fangxin Liu; Ning Yang; Zhiyan Song; Zongwu Wang; Li Jiang 002 (ICCD, 2024)

PS4: A Low Power SNN Accelerator with Spike Speculative Scheme. - Zongwu Wang; Fangxin Liu; Xin Tang; Li Jiang 002 (ICCD, 2024)

T-BUS: Taming Bipartite Unstructured Sparsity for Energy-Efficient DNN Acceleration. - Ning Yang; Fangxin Liu; Zongwu Wang; Zhiyan Song; Tao Yang 031; Li Jiang 002 (ICCD, 2024)

Ninja: A Hardware Assisted System for Accelerating Nested Address Translation. - Longyu Zhao; Zongwu Wang; Fangxin Liu; Li Jiang 002 (ICCD, 2024)

UM-PIM: DRAM-based PIM with Uniform & Shared Memory Space. - Yilong Zhao; Mingyu Gao 001; Fangxin Liu; Yiwei Hu; Zongwu Wang; Han Lin; Jin Li 002; He Xian; Hanlin Dong; Tao Yang 031; Naifeng Jing; Xiaoyao Liang; et al. (ISCA, 2024)

LowPASS: A Low power PIM-based accelerator with Speculative Scheme for SNNs. - Fangxin Liu; Shiyuan Huang; Longyu Zhao; Li Jiang 002; Zongwu Wang (ISLPED, 2024)

SRender: Boosting Neural Radiance Field Efficiency via Sensitivity-Aware Dynamic Precision Rendering. - Zhuoran Song; Houshu He; Fangxin Liu; Yifan Hao 001; Xinkai Song; Li Jiang 002; Xiaoyao Liang (MICRO, 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)

Phantom: Constraining Generative Artificial Intelligence Models for Practical Domain Specific Peripherals Trace Synthesizing. - Zhibai Huang; Yihan Shen; Yongchen Xie; Zhixiang Wei; Yun Wang; Fangxin Liu; Tao Song 003; Zhengwei Qi (CoRR, 2024)

TokenRing: An Efficient Parallelism Framework for Infinite-Context LLMs via Bidirectional Communication. - Zongwu Wang; Fangxin Liu; Mingshuai Li; Li Jiang 002 (CoRR, 2024)

ERA-BS: Boosting the Efficiency of ReRAM-Based PIM Accelerator With Fine-Grained Bit-Level Sparsity. - Fangxin Liu; Wenbo Zhao 005; Zongwu Wang; Yongbiao Chen; Xiaoyao Liang; Li Jiang 002 (IEEE Trans. Computers, 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)

Exploiting Differential-Based Data Encoding for Enhanced Query Efficiency. - Fangxin Liu; Zongwu Wang; Peng Xu; Shiyuan Huang; 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)

OPS: Outlier-Aware Precision-Slice Framework for LLM Acceleration. - Fangxin Liu; Ning Yang; Zongwu Wang; Xuanpeng Zhu; Haidong Yao; Xiankui Xiong; Qi Sun; Li Jiang 002 (DATE, 2025)

EVASION: Efficient KV CAche CompreSsion vIa PrOduct QuaNtization. - Zongwu Wang; Fangxin Liu; Peng Xu; Qingxiao Sun; Junping Zhao; Li Jiang 002 (DATE, 2025)

GSArch: Breaking Memory Barriers in 3D Gaussian Splatting Training via Architectural Support. - Houshu He; Gang Li 015; Fangxin Liu; Li Jiang 002; Xiaoyao Liang; Zhuoran Song (HPCA, 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)

Qtenon: Towards Low-Latency Architecture Integration for Accelerating Hybrid Quantum-Classical Computing. - Chenning Tao; Liqiang Lu; Size Zheng 001; Li-Wen Chang; Minghua Shen; Hanyu Zhang; Fangxin Liu; Kaiwen Zhou; Jianwei Yin (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)

SpMMPlu-Pro: An Enhanced Compiler Plug-In for Efficient SpMM and Sparsity Propagation Algorithm. - Shiyuan Huang; Fangxin Liu; Tao Yang 031; Zongwu Wang; Ning Yang; Li Jiang 002 (IEEE Trans. Comput. Aided Des. Integr. Circuits 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)

gCom: Fine-grained Compressors in Graphics Memory of Mobile GPU. - Dongjie Tang; Zijun Wu; Yun Wang; Yicheng Gu; Fangxin Liu; Zhengwei Qi (ACM Trans. Archit. Code Optim., 2025)

MILLION: Mastering Long-Context LLM Inference Via Outlier-Immunized KV Product Quantization. - Zongwu Wang; Peng Xu; Fangxin Liu; Yiwei Hu; Qingxiao Sun; Gezi Li; Cheng Li; Xuan Wang; Li Jiang 002; Haibing Guan (CoRR, 2025)

DASH: Input-Aware Dynamic Layer Skipping for Efficient LLM Inference with Markov Decision Policies. - Ning Yang; Fangxin Liu; Junjie Wang; Tao Yang 031; Kang Liu 001; Haibing Guan; Li Jiang 002 (CoRR, 2025)

HyCTor: A Hybrid CNN-Transformer Network Accelerator With Flexible Weight/Output Stationary Dataflow and Multicore Extension. - Shuai Yuan 016; Weifeng He; Zhenhua Zhu; Fangxin Liu; Zhuoran Song; Guohao Dai; Guanghui He; Yanan Sun 003 (IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 2025)

Flexible Operator Fusion for Fast Sparse Transformer with Diverse Masking on GPU. - Wenhao Dai; Haodong Deng; Mengfei Rong; Xinyu Yang; Hongyu Liu; Fangxin Liu; Hailong Yang; Weifeng Liu; Qingxiao Sun (CoRR, 2025)

FlexQuant: A Flexible and Efficient Dynamic Precision Switching Framework for LLM Quantization. - Fangxin Liu; Zongwu Wang; JinHong Xia; Junping Zhao; Jian Liu; Haibing Guan; Li Jiang 002 (CoRR, 2025)

LCD: Advancing Extreme Low-Bit Clustering for Large Language Models via Knowledge Distillation. - Fangxin Liu; Ning Yang; Junping Zhao; Tao Yang 031; Haibing Guan; Li Jiang 002 (CoRR, 2025)

RTSA: A Run-Through Sparse Attention Framework for Video Transformer. - Xuhang Wang; Zhuoran Song; Chunyu Qi; Fangxin Liu; Naifeng Jing; Li Jiang 002; Xiaoyao Liang (IEEE Trans. Computers, 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)

PUSHtap: PIM-based In-Memory HTAP with Unified Data Storage Format. - Yilong Zhao; Mingyu Gao 001; Huanchen Zhang; Fangxin Liu; Gongye Chen; He Xian; Haibing Guan; Li Jiang 002 (CoRR, 2025)