dynamic delay 1parameter efficiency 1speech recognition 1spiking neural networks 1temporal processing 1
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cs.CV2026
BSViT: A Burst Spiking Vision Transformer for Expressive and Efficient Visual Representation Learning
Hongxiang Peng, Dewei Bai, Hong Qu
Spiking Vision Transformers (S-ViTs) offer a promising framework for energy-efficient visual learning. However, existing designs remain limited by two fundamental issues: the restr…
cs.CV2026
QB-LIF: Learnable-Scale Quantized Burst Neurons for Efficient SNNs
Dewei Bai, Hongxiang Peng, Jiajun Mei +4
Binary spike coding enables sparse and event-driven computation in spiking neural networks (SNNs), yet its 1-bit-per-timestep representation fundamentally limits information throug…
cs.CV2026
Vision SmolMamba: Spike-Guided Token Pruning for Energy-Efficient Spiking State-Space Vision Models
Dewei Bai, Hongxiang Peng, Yunyun Zeng +3
Spiking Transformers have shown strong potential for long-range visual modeling through spike-driven self-attention. However, their quadratic token interactions remain fundamentall…