AI RESEARCH
Threshold Modulation for Online Test-Time Adaptation of Spiking Neural Networks
arXiv CS.AI
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ArXi:2505.05375v3 Announce Type: replace-cross Recently, spiking neural networks (SNNs), deployed on neuromorphic chips, provide highly efficient solutions on edge devices in different scenarios. However, their ability to adapt to distribution shifts after deployment has become a crucial challenge. Online test-time adaptation (OTTA) offers a promising solution by enabling models to dynamically adjust to new data distributions without requiring source data or labeled target samples.