Vector Normalization

Vector normalization is particularly important in retrieval systems that rely on cosine similarity or related metrics. It can reduce side effects caused by vector magnitude and make semantic comparison more stable. However, it is not automatically necessary for every embedding type; the model-generation logic must be considered. For that reason, normalization is a subtle but powerful preprocessing choice that affects retrieval correctness.