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Leveraging MLLMs without any training, this framework achieves competitive audio-guided video segmentation, showcasing the power of foundation models in practical applications.
SPWM cuts computational costs and energy consumption in image restoration tasks while maintaining high image quality, showcasing the untapped potential of spiking neural networks.
Distilling knowledge from a heavy teacher model into a lightweight student via dual-branch distillation lets UAV trackers maintain accuracy while drastically reducing computation.
