SVL pretraining enables SNNs to reach 85.4% top-1 accuracy on zero-shot 3D classification while outperforming prior SNNs on detection, segmentation, and action recognition with added open-world QA capability.
Integer-valued training and spike-driven inference spiking neural network for high-performance and energy-efficient object detection
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LIFE is a proposed agentic framework that combines four components to enable incremental, flexible, and energy-efficient continual learning for HPC operations such as latency spike mitigation.
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SVL: Spike-based Vision-language Pretraining for Efficient 3D Open-world Understanding
SVL pretraining enables SNNs to reach 85.4% top-1 accuracy on zero-shot 3D classification while outperforming prior SNNs on detection, segmentation, and action recognition with added open-world QA capability.
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LIFE -- an energy efficient advanced continual learning agentic AI framework for frontier systems
LIFE is a proposed agentic framework that combines four components to enable incremental, flexible, and energy-efficient continual learning for HPC operations such as latency spike mitigation.