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Inverse distance weighting attention

2023-10-28 · Calvin Mccarter

We report the effects of replacing the scaled dot-product (within softmax) attention with the negative-log of Euclidean distance. This form of attention simplifies to inverse distance weighting interpolation. Used in simple one hidden layer networks and trained with vanilla cross-entropy loss on classification problems, it tends to produce a key matrix containing prototypes and a value matrix with corresponding logits. We also show that the resulting interpretable networks can be augmented with manually-constructed prototypes to perform low-impact handling of special cases.

📄 PDF Abstract BibTeX arXiv:2310.18805

Code (1)

calvinmccarter/idw-attention 공식 구현 pytorch

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