A statistical risk estimation method enables query-specific dimension selection in dense embeddings, achieving equivalent effectiveness with about 50% smaller embeddings at inference time.
InFind- ings of the Association for Computational Linguistics: EMNLP 2022, pages 1286–1304, Abu Dhabi, United Arab Emirates
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Statistical Foundations of DIME: Risk Estimation for Practical Index Selection
A statistical risk estimation method enables query-specific dimension selection in dense embeddings, achieving equivalent effectiveness with about 50% smaller embeddings at inference time.