Cover Image

Efficient ANN-Guided Distillation: Aligning Rate-based Features of Spiking Neural Networks through Hybrid Block-wise Replacement

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Yang, Shu, Yu, Chengting, Liu, Lei, Ma, Hanzhi, Wang, Aili, Li, Erping
Format:	Preprint
Published:	2025
Subjects:	Machine Learning Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Advancing Training Efficiency of Deep Spiking Neural Networks through Rate-based Backpropagation
by: Yu, Chengting, et al.
Published: (2024)

Efficient Logit-based Knowledge Distillation of Deep Spiking Neural Networks for Full-Range Timestep Deployment
by: Yu, Chengting, et al.
Published: (2025)

Improving Quantization-aware Training of Low-Precision Network via Block Replacement on Full-Precision Counterpart
by: Yu, Chengting, et al.
Published: (2024)

Enhanced Self-Distillation Framework for Efficient Spiking Neural Network Training
by: Zhao, Xiaochen, et al.
Published: (2025)

Go beyond End-to-End Training: Boosting Greedy Local Learning with Context Supply
by: Yu, Chengting, et al.
Published: (2023)

SDiT: Spiking Diffusion Model with Transformer
by: Yang, Shu, et al.
Published: (2024)

Decoupling Dark Knowledge via Block-wise Logit Distillation for Feature-level Alignment
by: Yu, Chengting, et al.
Published: (2024)

Temporal Separation with Entropy Regularization for Knowledge Distillation in Spiking Neural Networks
by: Yu, Kairong, et al.
Published: (2025)

Towards Low-latency Event-based Visual Recognition with Hybrid Step-wise Distillation Spiking Neural Networks
by: Zhong, Xian, et al.
Published: (2024)

Fast Tensorization of Neural Networks via Slice-wise Feature Distillation
by: Hamreras, Safa, et al.
Published: (2026)

STI-SNN: A 0.14 GOPS/W/PE Single-Timestep Inference FPGA-based SNN Accelerator with Algorithm and Hardware Co-Design
by: Wang, Kainan, et al.
Published: (2025)

Efficient Speech Command Recognition Leveraging Spiking Neural Network and Curriculum Learning-based Knowledge Distillation
by: Wang, Jiaqi, et al.
Published: (2024)

DTA: Dual Temporal-channel-wise Attention for Spiking Neural Networks
by: Kim, Minje, et al.
Published: (2025)

ReSpike: Residual Frames-based Hybrid Spiking Neural Networks for Efficient Action Recognition
by: Xiao, Shiting, et al.
Published: (2024)

Novel Physics-Aware Attention-Based Machine Learning Approach for Mutual Coupling Modeling
by: Wang, Can, et al.
Published: (2025)

Self-cross Feature based Spiking Neural Networks for Efficient Few-shot Learning
by: Xu, Qi, et al.
Published: (2025)

Activation-wise Propagation: A One-Timestep Strategy for Spiking Neural Networks
by: Song, Jian, et al.
Published: (2025)

STARS: Spike Tail-Aware Relational Synthesis for ANN-to-SNN Data-Free Knowledge Distillation
by: Ye, Shuhan, et al.
Published: (2026)

FastFLUX: Pruning FLUX with Block-wise Replacement and Sandwich Training
by: Cai, Fuhan, et al.
Published: (2025)

Noise Adaptor: Enhancing Low-Latency Spiking Neural Networks through Noise-Injected Low-Bit ANN Conversion
by: Li, Chen, et al.
Published: (2024)

On Reducing Activity with Distillation and Regularization for Energy Efficient Spiking Neural Networks
by: Louis, Thomas, et al.
Published: (2024)

PLAF: Pixel-wise Language-Aligned Feature Extraction for Efficient 3D Scene Understanding
by: Wen, Junjie, et al.
Published: (2026)

DiffusionBlocks: Block-wise Neural Network Training via Diffusion Interpretation
by: Shing, Makoto, et al.
Published: (2025)

Neural Architecture Search of Time-to-First-Spike-Coded Spiking Neural Networks for Efficient Eye-based Emotion Recognition
by: Liu, Qianhui, et al.
Published: (2025)

Self-Distillation Learning Based on Temporal-Spatial Consistency for Spiking Neural Networks
by: Zuo, Lin, et al.
Published: (2024)

Complex-Valued Neural Network based Federated Learning for Multi-user Indoor Positioning Performance Optimization
by: Yu, Hanzhi, et al.
Published: (2024)

Hybrid Layer-Wise ANN-SNN With Surrogate Spike Encoding-Decoding Structure
by: Luu, Nhan T., et al.
Published: (2025)

Efficient Training of Spiking Neural Networks by Spike-aware Data Pruning
by: Ma, Chenxiang, et al.
Published: (2025)

Random Feature Spiking Neural Networks
by: Gollwitzer, Maximilian, et al.
Published: (2025)

Parallel Spiking Unit for Efficient Training of Spiking Neural Networks
by: Li, Yang, et al.
Published: (2024)

StreamFlow: Streaming Flow Matching with Block-wise Guided Attention Mask for Speech Token Decoding
by: Guo, Dake, et al.
Published: (2025)

Distill-then-Replace: Efficient Task-Specific Hybrid Attention Model Construction
by: Xia, Xiaojie, et al.
Published: (2026)

Faster and Stronger: When ANN-SNN Conversion Meets Parallel Spiking Calculation
by: Hao, Zecheng, et al.
Published: (2024)

Beyond Rate Coding: Surrogate Gradients Enable Spike Timing Learning in Spiking Neural Networks
by: Yu, Ziqiao, et al.
Published: (2025)

STAER: Temporal Aligned Rehearsal for Continual Spiking Neural Network
by: Gianferrari, Matteo, et al.
Published: (2026)

Integer-State Dynamics of Quantized Spiking Neural Networks for Efficient Hardware Acceleration
by: Zhang, Lei
Published: (2026)

Head-Tail-Aware KL Divergence in Knowledge Distillation for Spiking Neural Networks
by: Zhang, Tianqing, et al.
Published: (2025)

Efficiently Training Time-to-First-Spike Spiking Neural Networks from Scratch
by: Che, Kaiwei, et al.
Published: (2024)

Efficient and Flexible Neural Network Training through Layer-wise Feedback Propagation
by: Weber, Leander, et al.
Published: (2023)

Spiking CenterNet: A Distillation-boosted Spiking Neural Network for Object Detection
by: Bodden, Lennard, et al.
Published: (2024)