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Are Transformers with One Layer Self-Attention Using Low-Rank Weight Matrices Universal Approximators?
Existing analyses of the expressive capacity of Transformer models have required excessively deep layers for data memorization, leading to a discrepancy with the Transformers actually used in practice.
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