Gated MLPs as Symmetry-Broken Rank-1 Bilinear Attention
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Abstract (arXiv)
We show that the conventional gated MLP can be viewed as a rank-1 approximation to a bilinear attention mechanism with two distinct factors corresponding to the query and the key. We further show that moving the nonlinearity onto one factor breaks the exchange symmetry between the two factors and, for non-homogeneous activations, the inverse-scaling symmetry as well. This perspective may help explain why gated MLPs are effective in practice and inform the design of future architectures.
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References · 3
- 2020GLU Variants Improve Transformercited by 1,724
- 2020Transformer Feed-Forward Layers Are Key-Value Memoriescited by 1,307
- 2016Language Modeling with Gated Convolutional Networkscited by 688
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