Training-Free Uncertainty Estimation for Embedding Models
The method estimates how reliable an embedding model's representation is for future tasks without knowing those tasks beforehand. It achieves this by checking if a test point has neighbors that are consistently close to it across multiple different embedding spaces. This provides a way to gauge representation quality even without ground truth labels.