6 papers
SpikCommander: A High-performance Spiking Transformer with Multi-view Learning for Efficient Speech Command Recognition
Jiaqi Wang, Liutao Yu, Xiongri Shen +6
Spiking neural networks (SNNs) offer a promising path toward energy-efficient speech command recognition (SCR) by leveraging their event-driven processing paradigm. However, existi…
SM-Former: Spiking Symmetric Mixing Branchformer for Brain Auditory Attention Detection
Jiaqi Wang, Zhengyu Ma, Xiongri Shen +7
Auditory attention detection (AAD) aims to decode listeners' focus in complex auditory environments from electroencephalography (EEG) recordings, which is crucial for developing ne…
E2ATST: A Temporal-Spatial Optimized Energy-Efficient Architecture for Training Spiking Transformer
Yunhao Ma, Yanyu Lin, Mingjing Li +9
(1) Pengcheng Laboratory, (2) Southern University of Science and Technology, (3) Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, (4) University of Chinese…
A Survey of Context Engineering for Large Language Models
Lingrui Mei, Jiayu Yao, Yuyao Ge +12
The performance of Large Language Models (LLMs) is fundamentally determined by the contextual information provided during inference. This survey introduces Context Engineering, a f…
MSVIT: Improving Spiking Vision Transformer Using Multi-scale Attention Fusion
Wei Hua, Chenlin Zhou, Jibin Wu +2
The combination of Spiking Neural Networks (SNNs) with Vision Transformer architectures has garnered significant attention due to their potential for energy-efficient and high-perf…
Efficient Speech Command Recognition Leveraging Spiking Neural Network and Curriculum Learning-based Knowledge Distillation
Jiaqi Wang, Liutao Yu, Liwei Huang +6
The intrinsic dynamics and event-driven nature of spiking neural networks (SNNs) make them excel in processing temporal information by naturally utilizing embedded time sequences a…