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DiffPDE achieves faster and more accurate PDE code repair by focusing only on localized errors, challenging the inefficiencies of existing autoregressive methods.
Depth integration in audio-visual segmentation leads to over 10% performance gains, revealing a critical yet overlooked modality in multimodal perception.