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Comparing embedding models with synthetic query probing [R]

Reddit r/MachineLearning · yesterday

The authors propose Synthetic Query Probing, a simple yet effective approach to compare different embedding models by comparing similarity match scores across models instead of raw embedding spaces. The paper illustrates non-linear relationships between models like Ada and Titan, offering practical guidance for swapping embedding models and setting retrieval thresholds.

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