Blaise Delattre
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126
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ML×1NLP×1
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2026
Trading Complexity for Expressivity Through Structured Generalized Linear Token Mixing
The paper proposes a unified framework for designing efficient and expressive token mixing layers by separating the direct and recurrent influences of inputs, allowing for a principled trade-off between computational complexity and model expressivity.
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