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New MeMark technique embeds watermarks in SNN neuron states

By PulseAugur Editorial · [1 sources] ·

Researchers have developed a new watermarking technique called MeMark for Spiking Neural Networks (SNNs) to protect against unauthorized reuse of pre-trained models. Unlike previous methods that focused on output verification, MeMark embeds a multi-bit identifier within the internal membrane state of selected Leaky Integrate-and-Fire (LIF) neurons. This approach allows for verification without needing a learned decoder and has demonstrated resilience against various attacks, including fine-tuning, pruning, quantization, and output-head replacement, as tested on a large SpikeGPT checkpoint. AI

IMPACT This watermarking method could enhance intellectual property protection for AI models, particularly in the growing field of Spiking Neural Networks.

RANK_REASON The cluster contains an academic paper detailing a new technical method for watermarking AI models. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.LG →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

New MeMark technique embeds watermarks in SNN neuron states

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The cluster contains an academic paper detailing a new technical method for watermarking AI models. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.LG TIER_1 English(EN) · Roberto Ria\~no, Gorka Abad, Stjepan Picek, Aitor Urbieta ·

    MeMark: Membrane-Space Watermarking for Spiking Neural Networks

    arXiv:2608.25738v1 Announce Type: cross Abstract: Spiking Neural Networks (SNNs) are increasingly distributed as pretrained checkpoints and reused as backbones for new tasks. However, current SNN watermarks are mainly verified against the model output. Thus, a user who replaces t…

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