1 citations · 2 across the 5 of their papers we have counts for
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SpikingMamba: Towards Energy-Efficient Large Language Models via Knowledge Distillation from Mamba
Yulong Huang, Jianxiong Tang, Chao Wang +5
Large Language Models (LLMs) have achieved remarkable performance across tasks but remain energy-intensive due to dense matrix operations. Spiking neural networks (SNNs) improve en…
PRF: Parallel Resonate and Fire Neuron for Long Sequence Learning in Spiking Neural Networks
Yulong Huang, Zunchang Liu, Changchun Feng +6
Recently, there is growing demand for effective and efficient long sequence modeling, with State Space Models (SSMs) proving to be effective for long sequence tasks. To further red…
CLIF: Complementary Leaky Integrate-and-Fire Neuron for Spiking Neural Networks
Yulong Huang, Xiaopeng Lin, Hongwei Ren +5
Spiking neural networks (SNNs) are promising brain-inspired energy-efficient models. Compared to conventional deep Artificial Neural Networks (ANNs), SNNs exhibit superior efficien…