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.
Asymptotic analysis of two-layer neural networks after one gradient step under gaussian mixtures data with structure.arXiv preprint arXiv:2503.00856
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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.