Spiking Transformer
PulseAugur coverage of Spiking Transformer — every cluster mentioning Spiking Transformer across labs, papers, and developer communities, ranked by signal.
-
Spikformer V2 achieves 80%+ accuracy on ImageNet using SNNs
Researchers have developed Spikformer V2, a novel Spiking Neural Network (SNN) that incorporates a Spiking Self-Attention mechanism. This advancement allows SNNs to leverage the performance benefits of self-attention, p…
-
New methods enhance Spiking Transformer performance on image tasks · 2 sources tracked
Researchers have introduced Spiking Local Interaction (SLI) and Adaptive Complementary Fusion (ACF) to enhance Spiking Transformers. These methods address limitations in standard Spiking Self-Attention (SSA) by introduc…
-
New Ge2mS-T architecture boosts energy efficiency in Spiking Transformers
Researchers have introduced Ge$^2$mS-T, a novel architecture designed to enhance the energy efficiency of Spiking Vision Transformers (S-ViTs). This new approach addresses limitations in existing methods by implementing…
-
New Spiking Transformer Achieves State-of-the-Art Efficiency
Researchers have introduced SAFformer, a novel Spiking Transformer architecture designed to improve energy efficiency and performance in visual data processing. By adopting an active predictive filtering paradigm inspir…