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Beihang University
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LLMs can now generate more accurate and complex CAD models by pointing to existing geometric entities, rather than relying on discretized command sequences prone to topological errors.
By strategically dropping "anchor" Gaussians and their neighbors, DropAnSH-GS overcomes the limitations of naive dropout in 3D Gaussian Splatting, leading to more robust and globally informed scene representations under sparse-view conditions.
