SAGE: Surrogate-gradient adaptation via attention-guided entropy for spiking transformers
Read the original at arxiv.org→arXiv:2608.13702v1 Announce Type: new Abstract: Spiking neural networks (SNNs) offer an energy-efficient alternative to conventional deep neural networks by exploiting sparse event-driven computation, but their...
Original headline: "SAGE: Surrogate-gradient Adaptation via Attention-Guided Entropy for Spiking Transformers"
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- Aug 17, 04:00 UTC arXiv cs.LG lead source SAGE: Surrogate-gradient Adaptation via Attention-Guided Entropy for Spiking Transformers