35 citations · 36 across the 7 of their papers we have counts for
Showing cs.NEShow all
2 papers · 1 filter
cs.NE2026
Winner-Take-All Spiking Transformer for Language Modeling
Chenlin Zhou, Sihang Guo, Jiaqi Wang +6
Spiking Transformers, which combine the scalability of Transformers with the sparse, energy-efficient property of Spiking Neural Networks (SNNs), have achieved impressive results i…
cs.NE2023★ 35 cited
Spikingformer: A Key Foundation Model for Spiking Neural Networks
Chenlin Zhou, Liutao Yu, Zhaokun Zhou +5
Spiking neural networks (SNNs) offer a promising energy-efficient alternative to artificial neural networks, due to their event-driven spiking computation. However, some foundation…