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Performance-Efficiency Tradeoffs in Transformers: An Approximation Theory Perspective
Transformers have achieved remarkable successes across a wide range of applications, yet the theoretical foundation of their model efficiency remains underexplored. In this work, we investigate how the model parameters -- mainly attention heads and head dimensions -- should be allocated across layer
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