What is neural embedding space geometry?

It refers to how learned representations are structured in high-dimensional space.

Embedding spaces encode semantic relationships as geometric properties such as distance, direction, and clustering. Linear relationships often emerge (e.g., word analogies). Proper training ensures separability and smooth manifolds.