StreamSplit: Continuous Audio Representation Learning via Uncertainty-Guided Adaptive Splitting 事件

StreamSplit: Continuous Audio Representation Learning via Uncertainty-Guided Adaptive Splitting arXiv:2605.26523v1 Announce Type: cross Abstract: Large-batch Contrastive Learning (CL), the foundation of modern representation learning, is fundamentally incompatible with the volatile resource constraints of edge devices. This conflict creates a dilemma: small on-device batches degrade model fidelity, while offloading to the cloud incurs unacceptable latency and bandwidth costs. Existing solutions