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Progressive semantic refinement no longer requires linear codebook memory growth: reusing a compact set of shared knowledge bases across residual stages achieves multi-depth transmission with a strictly bounded storage footprint.
EgoMed-Agent achieves over six times better segmentation accuracy than existing text-prompted methods by effectively aligning user intent with visual data in real-time.
