Chunk length and magnitude bias

Move from embedding whole documents to embedding passages and the top hit becomes the longest passage nearly every time, because a mean-pooling encoder gives long chunks long vectors and an inner-product index multiplies that length into every score. This chapter works the arithmetic on four real chunks, shows the one-line fix and the regression test that holds it, explains why capping chunk size only compresses the length distribution, and names what normalisation leaves untouched.

Vector arithmetic — read the current version at https://daviddominguez.dev/learn/en/vector-arithmetic/vector-store

Back to top