This note provides an interesting observation on casting partial least square (PLS) as a linearized self-attention so that PLS may be studied within the neural network paradigm. On the other hand, the dimensionality reduction and selection of predictors in PLS may indicate that self-attention includes certain degree of dimensionality normalization toward improved learning.
@article{arxiv.2605.28592,
title = {PLS in the Mirror of Self-Attention},
author = {Jiangsheng and You},
journal= {arXiv preprint arXiv:2605.28592},
year = {2026}
}