Attention pooling produces a free-multiplicative-convolution bulk spectrum and two phase transitions for signal recovery; optimal weights are the top eigenvector of the positional correlation matrix R.
In this limit, the companion transform admits a closed form and the outlier location simplifies to λout =β(1 +γ/(β−1))
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How Does Attention Help? Insights from Random Matrices on Signal Recovery from Sequence Models
Attention pooling produces a free-multiplicative-convolution bulk spectrum and two phase transitions for signal recovery; optimal weights are the top eigenvector of the positional correlation matrix R.