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Achieve massive gains in few-shot hierarchical multi-label classification (+42%) by adaptively balancing semantic priors and visual evidence using level-aware embeddings.
Despite high accuracy on synthetic data, machine learning models struggle to generalize to real-world 4D-STEM data for ferroelectric polarization mapping, highlighting a critical domain gap.
