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Asynchronous EEG event detection is solved by a novel multiscale discrete spatiotemporal tokenization that captures both brief and sustained neural dynamics, outperforming prior methods across diverse datasets.
SlimVLM achieves unprecedented efficiency in Vision-Language Models by intelligently pruning redundant visual tokens without sacrificing performance.