Zhanglu Yan

According to our database, Zhanglu Yan authored at least 20 papers between 2021 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2026

Kirin: Improving ANN efficiency with SNN Hybridization.

Chenyu Wang, Zhanglu Yan, Zhi Zhou, Xu Chen, Weng-Fai Wong

CoRR, February, 2026

Matterhorn: Efficient Analog Sparse Spiking Transformer Architecture with Masked Time-To-First-Spike Encoding.

Zhanglu Yan, Kaiwen Tang, Zixuan Zhu, Zhenyu Bai, Qianhui Liu, Weng-Fai Wong

CoRR, January, 2026

SpikySpace: A Spiking State Space Model for Energy-Efficient Time Series Forecasting.

Kaiwen Tang, Jiaqi Zheng, Yuze Jin, Yupeng Qiu, Guangda Sun, Zhanglu Yan, Weng-Fai Wong

CoRR, January, 2026

Energy-Efficient and Dequantization-Free Quantization of LLMs: A Spiking Neural Network Approach to Salient Value Mitigation.

Chenyu Wang, Zhanglu Yan, Zhi Zhou, Xu Chen, Weng-Fai Wong

Proceedings of the ACM Web Conference 2026, 2026

A Data-Driven Dynamic Execution Orchestration Architecture.

Zhenyu Bai, Pranav Dangi, Rohan Juneja, Zhaoying Li, Zhanglu Yan, Huiying Lan, Tulika Mitra

Proceedings of the 31st ACM International Conference on Architectural Support for Programming Languages and Operating Systems, 2026

2025

Energy-Efficient and Dequantization-Free Q-LLMs: A Spiking Neural Network Approach to Salient Value Mitigation.

Chenyu Wang, Zhanglu Yan, Zhi Zhou, Xu Chen, Weng-Fai Wong

CoRR, October, 2025

Otters: An Energy-Efficient SpikingTransformer via Optical Time-to-First-Spike Encoding.

Zhanglu Yan, Jiayi Mao, Qianhui Liu, Fanfan Li, Gang Pan, Tao Luo, Bowen Zhu, Weng-Fai Wong

CoRR, September, 2025

Low Latency Conversion of Artificial Neural Network Models to Rate-Encoded Spiking Neural Networks.

Zhanglu Yan, Kaiwen Tang, Jun Zhou, Weng-Fai Wong

IEEE Trans. Neural Networks Learn. Syst., August, 2025

Sorbet: A Neuromorphic Hardware-Compatible Transformer-Based Spiking Language Model.

Kaiwen Tang, Zhanglu Yan, Weng-Fai Wong

Proceedings of the Forty-second International Conference on Machine Learning, 2025

2024

Reconsidering the energy efficiency of spiking neural networks.

Zhanglu Yan, Zhenyu Bai, Weng-Fai Wong

CoRR, 2024

SparrowSNN: A Hardware/software Co-design for Energy Efficient ECG Classification.

Zhanglu Yan, Zhenyu Bai, Tulika Mitra, Weng-Fai Wong

CoRR, 2024

Integrating Deep Learning and Synthetic Biology: A Co-Design Approach for Enhancing Gene Expression via N-terminal Coding Sequences.

Zhanglu Yan, Weiran Chu, Yuhua Sheng, Kaiwen Tang, Shida Wang, Yanfeng Liu, Weng-Fai Wong

CoRR, 2024

OneSpike: Ultra-low latency spiking neural networks.

Kaiwen Tang, Zhanglu Yan, Weng-Fai Wong

Proceedings of the International Joint Conference on Neural Networks, 2024

2023

CQ$^{+}$+ Training: Minimizing Accuracy Loss in Conversion From Convolutional Neural Networks to Spiking Neural Networks.

Zhanglu Yan, Jun Zhou, Weng-Fai Wong

IEEE Trans. Pattern Anal. Mach. Intell., October, 2023

HyperSNN: A new efficient and robust deep learning model for resource constrained control applications.

Zhanglu Yan, Shida Wang, Kaiwen Tang, Weng-Fai Wong

CoRR, 2023

Improve Long-term Memory Learning Through Rescaling the Error Temporally.

Shida Wang, Zhanglu Yan

CoRR, 2023

Efficient Hyperdimensional Computing.

Zhanglu Yan, Shida Wang, Kaiwen Tang, Weng-Fai Wong

Proceedings of the Machine Learning and Knowledge Discovery in Databases: Research Track, 2023

2022

Low Latency Conversion of Artificial Neural Network Models to Rate-encoded Spiking Neural Networks.

Zhanglu Yan, Jun Zhou, Weng-Fai Wong

CoRR, 2022

2021

Energy efficient ECG classification with spiking neural network.

Zhanglu Yan, Jun Zhou, Weng-Fai Wong

Biomed. Signal Process. Control., 2021

Near Lossless Transfer Learning for Spiking Neural Networks.

Zhanglu Yan, Jun Zhou, Weng-Fai Wong

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021