The Dimensions of dimensionality
https://www.cell.com/trends/cognitive-sciences/fulltext/S1364-6613(24)00189-X#
Globally interpretable feature dimensions are one property, among others like prediction performance and compactness, that researchers can prioritize when inferring latent representations.
Multidimensional representational spaces can capture complex structures such as hierarchical relationships, lexical entailment, and compositional features.
Superficially different representations, such as graphs and multidimensional data, can capture the same structural relationships under appropriate settings.
The dimensionality of a representation conveys relatively little information on its own.
