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Zi-Xuan Zhu

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#machine learning Preprint Sep 2026

Latency and accuracy tradeoffs in Spiking Neural Networks

Spiking neural networks are attractive for low-power speech command recognition, yet their latency has received far less attention than their energy efficiency, and their multi-timestep execution is widely assumed to make them slower than quantized neural networks. This paper challenges the assumption that more local t...

Zhang-Lu Yan, Zi-Xuan Zhu, Kaiwen Tang et al. · 0 citations

Preprint Aug 2026

Lapis: Laplacian Spiking Attention via First-Spike Timing and Membrane Leakage

Lapis is proposed, a spiking attention mechanism that scores each token pair by the L1 distance between its query and key first-spike latency vectors under time-to-first-spike coding, and maps this distance to an affinity through a Laplacian kernel.

Kaiwen Tang, Jiaqi Zheng, Zi-Xuan Zhu et al. · 0 citations