RIPE-MambaSpike: Resolution-Independent Spiking-State-Space Interfaces for Parameter-Efficient Event-Based Vision

arXiv:2609.32537 · cs.CV, cs.NE · Submitted 2026-09-26 · Read on arXiv

cs.CV, cs.NE

Submitted: 2026-09-26

Updated: 2026-09-26

Code: https://github.com/MuhiminOsim/RIPE-MambaSpike

Terminology

• Accuracy — 42× in this paper · explained in 1 episode
• Benchmark — 27× in this paper · explained in 2 episodes
• Transformer — 18× in this paper · explained in 2 episodes
• Ablation — 16× in this paper · explained in 1 episode
• Pruning — 12× in this paper · explained in 4 episodes
• Spiking neural networks — 8× in this paper · explained in 2 episodes
• Consistency — 5× in this paper · explained in 3 episodes
• Decoupling — 5× in this paper · explained in 2 episodes
• Core — 3× in this paper · explained in 2 episodes
• In International Conference on Learning Representations — 3× in this paper
• Temporal Decoupled Modulation — 3× in this paper
• Distillation — 2× in this paper · explained in 2 episodes
• In European Conference on Computer Vision — 2× in this paper
• Aggregation — 1× in this paper · explained in 1 episode
• Allocator — 1× in this paper · explained in 1 episode
• Conference on Computer Vision and Pattern Recognition — 1× in this paper
• Gradient Flow — 1× in this paper · explained in 2 episodes
• In International Conference on Machine Learning — 1× in this paper
• Regularization — 1× in this paper · explained in 3 episodes
• Representation Learning — 1× in this paper · explained in 2 episodes
• Sparse Attention — 1× in this paper · explained in 5 episodes
• Sparsity — 1× in this paper · explained in 4 episodes
• Spiking Neural Networks (SNNs) — 1× in this paper · explained in 3 episodes

Sources

• Vision SmolMamba: Spike-Guided Token Pruning for Energy-Efficient Spiking State-Space Vision Models
• FLAMES: A Hybrid Spiking-State Space Model for Adaptive Memory Retention in Event-Based Learning
• RepGhost: A Hardware-Efficient Ghost Module via Re-parameterization
• SpikMamba: When SNN meets Mamba in Event-based Human Action Recognition
• DarkShake-DVS: Event-based Human Action Recognition under Low-light andShaking Camera Conditions
• Spiking Wavelet Transformer
• Mamba: Linear-Time Sequence Modeling with Selective State Spaces
• SPARTA: Advancing Sparse Attention in Spiking Neural Networks via Spike-Timing-Based Prioritization
• Revisiting Batch Normalization for Training Low-latency Deep Spiking Neural Networks from Scratch
• A Simple Way to Initialize Recurrent Networks of Rectified Linear Units
• Spiking Transformer with Spatial-Temporal Attention
• SpikePool: Event-driven Spiking Transformer with Pooling Attention
• Mamba-Spike: Enhancing the Mamba Architecture with a Spiking Front-End for Efficient Temporal Data Processing
• RTFormer: Re-parameter TSBN Spiking Transformer
• Event Stream based Human Action Recognition: A High-Definition Benchmark Dataset and Algorithms
• TP-Spikformer: Token Pruned Spiking Transformer
• TS-SNN: Temporal Shift Module for Spiking Neural Networks
• QKFormer: Hierarchical Spiking Transformer using Q-K Attention

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