Make UMAP and embeddings cool again
Taking a short break from LLM research to go back to my roots.
Introducing... Concept Lenses! A training-free way to do similarity search along whatever concept you care about.
Typically, embedding-based similarity search is constrained by whatever notion of similarity the model learned in training. This means that if the model is primed for semantic similarity, but you actually care more about visual appearance, you'd need to switch models.
Under a Concept Lens projection, though, distance between embeddings means distance only along the concept you care about.
Blog post:
Demo:
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