What is embedding drift and how is it evaluated?

Embedding drift measures changes in vector representations over time.

Embedding drift occurs when semantic representations shift due to model updates or data changes. It is measured using cosine similarity distributions, centroid shifts, or MMD. It impacts downstream tasks like search, clustering, and recommendation systems.