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The University of Hong Kong
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GEM-Occ transforms transient visual geometry into a robust semantic occupancy memory, achieving superior performance in indoor mapping tasks.
Hierarchical latent actions in HiMem-WAM boost long-horizon manipulation robustness, outperforming existing models in real-world scenarios.
LargeMonitor achieves robust, zero-shot drift detection and dynamic adaptation in online continual learning, outperforming traditional methods that are blind to the structural causes of data shifts.
