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1. summation-based-transformers summation-based-transformers Public

   Linear-time sequence modeling that replaces attention's O(n²d) complexity with O(nd) summation-based aggregation. Demonstrates constraint-driven emergence: how functional representations can develo…

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2. attention-driven-transformers attention-driven-transformers Public

   Attention-Driven Transformers replace most attention layers with simple linear–activation blocks, keeping a single top attention layer to drive global representation learning. This design improves …

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3. residual-coupling residual-coupling Public

   Residual Coupling (RC): connecting frozen language models through learned bridge projections without modifying any weights.

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