Circuit duplication on frozen DINOv3 embeddings raises macro F1 to 0.875 on AQUA20, within 1.4 points of supervised ConvNeXt, with class-specific circuits helping 75% of species.
Learning from labeled and unlabeled data with label propagation.Technical Report CMU-CALD-02-107
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Inference-Path Optimization via Circuit Duplication in Frozen Visual Transformers for Marine Species Classification
Circuit duplication on frozen DINOv3 embeddings raises macro F1 to 0.875 on AQUA20, within 1.4 points of supervised ConvNeXt, with class-specific circuits helping 75% of species.