1 link tagged with all of: machine-learning + embeddings + information-retrieval
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Dimension Importance Estimation (DIME) is a framework designed to enhance dense information retrieval by identifying and pruning irrelevant dimensions from query embeddings. The article discusses various DIME approaches, including Magnitude DIME and Pseudo-Relevance Feedback DIME, which utilize different methods to assess the importance of dimensions and improve retrieval accuracy without requiring retraining or reindexing.
information-retrieval ✓
embeddings ✓
+ dimensionality-reduction
machine-learning ✓
+ retrieval-optimization