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MoE architectures outperform dense models in quantization resilience, revealing that structure trumps size in on-device VLM performance.
Achieve SE(3) equivariance and memory scalability in point cloud analysis with coordinate-based kernels, outperforming state-of-the-art equivariant methods on diverse tasks.
Voronoi cells and whitening can be combined to create LiDAR place recognition descriptors that implicitly measure Mahalanobis distance, improving performance on standard benchmarks.
