The Dimensional Ceiling of Single-Vector Embedding Retrieval
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Embedding-based retrieval hits a hard top-k capacity ceiling set by embedding dimension, and real systems already run into it.
The science and engineering of searching, indexing, and retrieving relevant information from large collections, including dense retrieval, sparse methods, and hybrid approaches.
Embedding-based retrieval hits a hard top-k capacity ceiling set by embedding dimension, and real systems already run into it.