Yongsheng Huang — accepted AI-conference papers

2026

Many Eyes, One Mind: Temporal Multi-Perspective and Progressive Distillation for Spiking Neural Networks

Kai Sun, Peibo Duan, Levin Kuhlmann, Yongsheng Huang, Nanxu Gong

ICLR 2026poster

Spiking Neural Networks (SNNs), inspired by biological neurons, are attractive for their event-driven energy efficiency but still fall short of Artificial Neural Networks (ANNs) in accuracy. Knowledge distillation (KD) has emerged as a promising approach to narrow this gap by transferring ANN knowle…

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2026

Not All Timesteps Matter Equally: Selective Alignment Knowledge Distillation for Spiking Neural Networks

Kai Sun, Peibo Duan, Yongsheng Huang, Guowei Zhang, Benjamin Smith, Nanxu Gong +1

IJCAI 2026

Spiking neural networks (SNNs), which are brain-inspired and spike-driven, achieve high energy efficiency. However, a performance gap between SNNs and artificial neural networks (ANNs) still remains. Knowledge distillation (KD) is commonly adopted to improve SNN performance, but existing methods typ

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