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GMBFormer achieves state-of-the-art urban green-space extraction by leveraging a global memory bank that enhances semantic reuse without compromising on visual fidelity.
MV-HGNN achieves superior 3D shape retrieval by effectively leveraging geometric dependencies and semantic alignment, outperforming existing methods in zero-shot settings.
LLMs can boost autonomous driving behavior classification accuracy to over 94% by fusing numerical time-series data with high-level semantic features.
