Synthetic Query Probing: Comparing Similarity Spaces Across Embeddings
pppeer · reddit · 2026-08-10
When swapping embedding models, how do you evaluate score differences and retrieval thresholds? The author proposes a simple method called "Synthetic Query Probing."
Since vector spaces aren't directly comparable, this approach compares their similarity spaces: calculating match scores for pairs of (synthetic question, chunk) across models. Experiments show that scores from different-dimensional Titan models are linearly related, whereas the relationship between Titan and Ada is non-linear with distinct ranges. This method helps in setting appropriate thresholds when migrating models.
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