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A neural architecture that performs semantic compression using nuclear diversity preservation, operating in pure vector space to bypass linguistic tokenization while maintaining conceptual understanding. The system compresses high-dimensional embeddings (e.g., 384D → 256D) through a teacher-student knowledge distillation framework that employs extreme weighting to prevent mode collapse, creating mathematical "semantic GPS coordinates" where related concepts cluster in measurable dimensional neighborhoods.
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