Image de couverture de livre

SpikeZIP-TF: Conversion is All You Need for Transformer-based SNN

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	You, Kang, Xu, Zekai, Nie, Chen, Deng, Zhijie, Guo, Qinghai, Wang, Xiang, He, Zhezhi
Format:	Preprint
Publié:	2024
Sujets:	Neural and Evolutionary Computing Artificial Intelligence
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

BKDSNN: Enhancing the Performance of Learning-based Spiking Neural Networks Training with Blurred Knowledge Distillation
par: Xu, Zekai, et autres
Publié: (2024)

Metaheuristics is All You Need
par: Cuicizion, Eliuvish, et autres
Publié: (2024)

ASRC-SNN: Adaptive Skip Recurrent Connection Spiking Neural Network
par: Xu, Shang, et autres
Publié: (2025)

One-Spike SNN: Single-Spike Phase Coding with Base Manipulation for ANN-to-SNN Conversion Loss Minimization
par: Hwang, Sangwoo, et autres
Publié: (2024)

MorphSNN: Adaptive Graph Diffusion and Structural Plasticity for Spiking Neural Networks
par: Huang, Yongsheng, et autres
Publié: (2026)

Optimal ANN-SNN Conversion with Group Neurons
par: Lv, Liuzhenghao, et autres
Publié: (2024)

Winner-Take-All Spiking Transformer for Language Modeling
par: Zhou, Chenlin, et autres
Publié: (2026)

CogniSNN: An Exploration to Random Graph Architecture based Spiking Neural Networks with Enhanced Depth-Scalability and Path-Plasticity
par: Huang, Yongsheng, et autres
Publié: (2025)

TT-SNN: Tensor Train Decomposition for Efficient Spiking Neural Network Training
par: Lee, Donghyun, et autres
Publié: (2024)

MD-SNN: Membrane Potential-aware Distillation on Quantized Spiking Neural Network
par: Lee, Donghyun, et autres
Publié: (2025)

Sparse Spiking Neural Network: Exploiting Heterogeneity in Timescales for Pruning Recurrent SNN
par: Chakraborty, Biswadeep, et autres
Publié: (2024)

PASCAL: Precise and Efficient ANN- SNN Conversion using Spike Accumulation and Adaptive Layerwise Activation
par: Ramesh, Pranav, et autres
Publié: (2025)

TS-SNN: Temporal Shift Module for Spiking Neural Networks
par: Yu, Kairong, et autres
Publié: (2025)

Faster and Stronger: When ANN-SNN Conversion Meets Parallel Spiking Calculation
par: Hao, Zecheng, et autres
Publié: (2024)

Evolutionary Spiking Neural Networks: A Survey
par: Shen, Shuaijie, et autres
Publié: (2024)

Spiking Wavelet Transformer
par: Fang, Yuetong, et autres
Publié: (2024)

A Multiplication-Free Spike-Time Learning Algorithm and its Efficient FPGA Implementation for On-Chip SNN Training
par: Mirsadeghi, Maryam, et autres
Publié: (2026)

Inference-Scale Complexity in ANN-SNN Conversion for High-Performance and Low-Power Applications
par: Bu, Tong, et autres
Publié: (2024)

An Asynchronous Multi-core Accelerator for SNN inference
par: Chen, Zhuo, et autres
Publié: (2024)

Parallel Spiking Unit for Efficient Training of Spiking Neural Networks
par: Li, Yang, et autres
Publié: (2024)

One-Timestep is Enough: Achieving High-performance ANN-to-SNN Conversion via Scale-and-Fire Neurons
par: Chen, Qiuyang, et autres
Publié: (2025)

Efficient ANN-SNN Conversion with Error Compensation Learning
par: Liu, Chang, et autres
Publié: (2025)

LitE-SNN: Designing Lightweight and Efficient Spiking Neural Network through Spatial-Temporal Compressive Network Search and Joint Optimization
par: Liu, Qianhui, et autres
Publié: (2024)

Cooperation Is All You Need
par: Adeel, Ahsan, et autres
Publié: (2023)

NSPDI-SNN: An efficient lightweight SNN based on nonlinear synaptic pruning and dendritic integration
par: Cai, Wuque, et autres
Publié: (2025)

SpikePool: Event-driven Spiking Transformer with Pooling Attention
par: Lee, Donghyun, et autres
Publié: (2025)

SNNF: An SNN-based Near-Sensor Noise Filter for Dynamic Vision Sensors
par: Yang, Yahan, et autres
Publié: (2026)

Quantization Meets Spikes: Lossless Conversion in the First Timestep via Polarity Multi-Spike Mapping
par: Zhang, Hangming, et autres
Publié: (2025)

Sign Gradient Descent-based Neuronal Dynamics: ANN-to-SNN Conversion Beyond ReLU Network
par: Oh, Hyunseok, et autres
Publié: (2024)

CogniSNN: Enabling Neuron-Expandability, Pathway-Reusability, and Dynamic-Configurability with Random Graph Architectures in Spiking Neural Networks
par: Huang, Yongsheng, et autres
Publié: (2025)

SkipSNN: Efficiently Classifying Spike Trains with Event-attention
par: Yin, Hang, et autres
Publié: (2024)

Spiking Transformer with Spatial-Temporal Attention
par: Lee, Donghyun, et autres
Publié: (2024)

Spiking Neural Networks with Consistent Mapping Relations Allow High-Accuracy Inference
par: Li, Yang, et autres
Publié: (2024)

BrainTransformers: SNN-LLM
par: Tang, Zhengzheng, et autres
Publié: (2024)

Natively neuromorphic LMU architecture for encoding-free SNN-based HAR on commercial edge devices
par: Fra, Vittorio, et autres
Publié: (2024)

Bishop: Sparsified Bundling Spiking Transformers on Heterogeneous Cores with Error-Constrained Pruning
par: Xu, Boxun, et autres
Publié: (2025)

Toward Relative Positional Encoding in Spiking Transformers
par: Lv, Changze, et autres
Publié: (2025)

RTFormer: Re-parameter TSBN Spiking Transformer
par: Wang, Hongzhi, et autres
Publié: (2024)

FSTA-SNN:Frequency-based Spatial-Temporal Attention Module for Spiking Neural Networks
par: Yu, Kairong, et autres
Publié: (2024)

NiSNN-A: Non-iterative Spiking Neural Networks with Attention with Application to Motor Imagery EEG Classification
par: Zhang, Chuhan, et autres
Publié: (2023)