3 papers
cs.AI2026
PTQ4SNN: Membrane-Aware Post-Training Quantization for Spiking Neural Networks
Hui Xie, Tong Shi, Haotong Qin +3
Spiking neural networks (SNNs) enable sparse and event-driven computation, but their low-bit deployment remains incomplete because recurrent membrane states are commonly retained i…
cs.CV2025
ReverB-SNN: Reversing Bit of the Weight and Activation for Spiking Neural Networks
Yufei Guo, Yuhan Zhang, Zhou Jie +5
The Spiking Neural Network (SNN), a biologically inspired neural network infrastructure, has garnered significant attention recently. SNNs utilize binary spike activations for effi…
cs.CV2025
Spiking Transformer:Introducing Accurate Addition-Only Spiking Self-Attention for Transformer
Yufei Guo, Xiaode Liu, Yuanpei Chen +3
Transformers have demonstrated outstanding performance across a wide range of tasks, owing to their self-attention mechanism, but they are highly energy-consuming. Spiking Neural N…