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  # Grid Geometric Classifier Proto
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  A prototype system for geometric primitive classification and text–geometry alignment. A voxel classifier learns to identify 38 shape classes from 5×5×5 binary occupancy grids using capacity cascades, curvature analysis, differentiation gates, and a rectified flow arbiter. A cross-contrast module then aligns the classifier's learned features with Qwen 2.5-1.5B text embeddings via InfoNCE, producing a shared latent space where geometric structure and natural language descriptions are jointly represented.
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  This is a research prototype exploring whether a geometric vocabulary learned from pure structure can meaningfully align with linguistic semantics.
 
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  # Grid Geometric Classifier Proto
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+ This is a subcomponent experiment for the larger scene classification experiments.
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  A prototype system for geometric primitive classification and text–geometry alignment. A voxel classifier learns to identify 38 shape classes from 5×5×5 binary occupancy grids using capacity cascades, curvature analysis, differentiation gates, and a rectified flow arbiter. A cross-contrast module then aligns the classifier's learned features with Qwen 2.5-1.5B text embeddings via InfoNCE, producing a shared latent space where geometric structure and natural language descriptions are jointly represented.
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  This is a research prototype exploring whether a geometric vocabulary learned from pure structure can meaningfully align with linguistic semantics.