Spike
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Related Articles from SNS
Spike-Aware C++ INT8 Inference for Sparse Spiking Language Models on Commodity CPUs
arXiv:2606.03026v1 Announce Type: new Abstract: Spiking language models expose activation sparsity that dense Transformer runtimes do not directly exploit. This paper studies that property from a systems perspective. Building on the SymbolicLight V1 spike-gated language model family, we implement a C++ CPU inference runtime that treats sparse binary spike states as an execution primitive rather than only applying post-hoc weight compression.
Massive Spikes in LLMs are Bias Vectors: Mechanistic Uncovering and Spike-Free Quantization
arXiv:2606.02288v1 Announce Type: new Abstract: Massive activation spikes in Large Language Models (LLMs) severely degrade quantization by stretching dynamic ranges. While prior hypotheses characterize these as high-level scalar biases, we argue that they are merely the scalar intermediates of rigid, structural vector biases in the spike-carrying tokens. We show that these tokens converge to constant vectors after normalization that drive the attention sink and value-state drain mechanisms.
A phage display library to dissect antibody responses to human coronavirus spike proteins
Coronaviruses are widespread human pathogens with demonstrated pandemic potential. We developed a phage immunoprecipitation sequencing (PhIP-Seq) library, C-Spike, enabling the profiling of serum antibody responses to coronavirus spike proteins. The C-Spike library includes peptides from 49 Alpha- and Betacoronavirus spike proteins, including pandemic coronaviruses (SARS-CoV-1, SARS-CoV-2, MERS-CoV), seasonal coronaviruses (HKU1, OC43, 229E, NL63), and selected animal coronaviruses of...
Quadratic integrate-and-fire neurons exhibit less fragmented loss landscapes and outperform leaky integrate-and-fire neurons in spike-based gradient descent
arXiv:2606.03935v1 Announce Type: new Abstract: The ability to train spiking neural networks is essential for modeling biological neural networks as well as for neuromorphic computing. However, for the extensively used leaky integrate-and-fire (LIF) neurons, arbitrarily small parameter changes can induce spike (dis)appearances that disrupt subsequent activity, leading to unstable neural representations and permanently silent neurons during exact spike-based gradient descent. Recent work...
A Retinomorphic Optical Spiking Neuron for Camouflaged Object Detection
arXiv:2606.00818v1 Announce Type: new Abstract: Advanced vision systems require retinomorphic, energy-efficient spike-based preprocessing of dynamic visual scenes. Here, we demonstrate multiple retinal preprocessing functionalities by leveraging a Hodgkin-Huxley-based optical spiking neuron (OSHN) that incorporates a two-dimensional anti-ambipolar phototransistor operated in the subthreshold regime to minimize power consumption. OSHN exhibits wavelength- and intensity-sensitive spike...
Energy-Efficient Implementation of Spiking Recurrent Cells on FPGA
arXiv:2605.10679v3 Announce Type: replace Abstract: Spiking Neural Networks (SNNs) can reduce energy consumption compared to conventional Artificial Neural Networks (ANNs) when spiking activity is sparse and the neuron model is hardware-friendly. However, biologically faithful models are often too costly to implement on FPGAs, whereas very simple models (e.g., IR/LIF) sacrifice part of the neuronal dynamics. In this work, we present an FPGA accelerator for an SNN using Spiking Recurrent Cell...
Signed Spiking Neuron Enabled by an Orthogonal-Easy-Axis Magnetic Tunnel Junction
Announce Type: new Abstract: Signed spiking neurons carry richer information than standard spiking neurons. This work proposes a compact magnetic tunnel junction (MTJ)-based neuron for signed leaky integrate-and-fire (LIF) operation. With orthogonal easy axes in the free and pinned layers, the device enables bipolar spike generation and maps magnetic-moment dynamics to signed LIF membrane-potential evolution.
Chronic cocaine exposure negatively impacts Long-COVID-like outcomes produced by the SARS-CoV-2 spike protein in the rat
Acute COVID-19 outcomes are exacerbated by substance use, however, the impact of substance use on Long-COVID is unknown. Here, we investigated the impact of chronic cocaine administration on spike-induced Long-COVID-like outcomes in the rat. Rats received intermittent chronic cocaine administration and a single intravenous injection of the SARS-CoV-2 spike protein.
On the Evaluation of Spiking Neural Network Configurations for Network Intrusion Detection
Announce Type: new Abstract: Network intrusion detection is a core component of modern cybersecurity infrastructure, yet the deep learning models that dominate the field are computationally demanding, motivating interest in lightweight alternatives suited to edge and neuromorphic deployment. Spiking Neural Networks (SNNs) are therefore a natural candidate, but their design space, spanning the choice of neuron model and spike encoding scheme, remains poorly characterized for intrusion...
SpikeReg: Energy-Efficient 3D Deformable Medical Image Registration with Spiking Neural Networks
arXiv:2605.25144v2 Announce Type: replace Abstract: Deformable medical image registration aligns anatomical structures across images but remains computationally dense at 3D resolution. Spiking neural networks (SNNs) offer sparse event-driven computation, yet have not been systematically studied for deformable medical image registration. We introduce SpikeReg, a spiking U-Net for 3D brain MRI registration.