6 papers
Otters++: A Time-to-first-spike Based Energy Efficient Optical Spiking Transformer
Zhanglu Yan, Jiayi Mao, Kaiwen Tang +6
Spiking neural networks (SNNs) are promising for energy-efficient inference, and time-to-first-spike (TTFS) coding is especially attractive because each neuron fires at most once.…
ShiftLIF: Efficient Multi-Level Spiking Neurons with Power-of-Two Quantization
Kaiwen Tang, Di Yu, Jiaqi Zheng +4
Spiking neural networks (SNNs) are promising for edge sensing due to their event-driven computation and temporal filtering capability. However, standard leaky integrate-and-fire (L…
Neural Architecture Search of Time-to-First-Spike-Coded Spiking Neural Networks for Efficient Eye-based Emotion Recognition
Qianhui Liu, Jing Yang, Miao Yu +4
Eye-based emotion recognition enables eyewear devices to perceive users' emotional states and support emotion-aware interaction. However, deploying such functionality on their reso…
Matterhorn: Masked Time-to-First-Spike Encoding by Reassigning the Silent State for Sparse and Energy-Efficient Spiking Transformers
Zhanglu Yan, Kaiwen Tang, Zixuan Zhu +4
Spiking neural networks (SNNs) promise energy-efficient inference for large language models (LLMs), yet most reported savings rely on compute-operation counts that overlook data mo…
Otters: An Energy-Efficient SpikingTransformer via Optical Time-to-First-Spike Encoding
Zhanglu Yan, Jiayi Mao, Qianhui Liu +5
Spiking neural networks (SNNs) promise high energy efficiency, particularly with time-to-first-spike (TTFS) encoding, which maximizes sparsity by emitting at most one spike per neu…
Human-Inspired Computing for Robust and Efficient Audio-Visual Speech Recognition
Qianhui Liu, Jiadong Wang, Yang Wang +3
Humans naturally perform audiovisual speech recognition (AVSR), enhancing the accuracy and robustness by integrating auditory and visual information. Spiking neural networks (SNNs)…