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cs.CV2026
Linearizing Vision Transformer with Test-Time Training
Yining Li, Dongchen Han, Zeyu Liu +3
While linear-complexity attention mechanisms offer a promising alternative to Softmax attention for overcoming the quadratic bottleneck, training such models from scratch remains p…
cs.CV2023
When Bio-Inspired Computing meets Deep Learning: Low-Latency, Accurate, & Energy-Efficient Spiking Neural Networks from Artificial Neural Networks
Gourav Datta, Zeyu Liu, James Diffenderfer +2
Bio-inspired Spiking Neural Networks (SNN) are now demonstrating comparable accuracy to intricate convolutional neural networks (CNN), all while delivering remarkable energy and la…
cs.CV2023★ 1 cited
Spiking Neural Networks with Dynamic Time Steps for Vision Transformers
Gourav Datta, Zeyu Liu, Anni Li +1
Spiking Neural Networks (SNNs) have emerged as a popular spatio-temporal computing paradigm for complex vision tasks. Recently proposed SNN training algorithms have significantly r…