Presents a structured generalized linear token mixing framework that extends recurrence equations to multiple past states, enabling new patterns with provable complexity-expressivity trade-offs for causal generation.
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Trading Complexity for Expressivity Through Structured Generalized Linear Token Mixing
Presents a structured generalized linear token mixing framework that extends recurrence equations to multiple past states, enabling new patterns with provable complexity-expressivity trade-offs for causal generation.