Definition
Sparse embeddings are high-dimensional vector representations where the vast majority of dimensions are zero, typically used in RAG to represent exact keyword importance and frequency (e.g., via BM25 or SPLADE). They provide a mechanism for precise lexical matching, acting as a technical counterbalance to the semantic 'fuzziness' of dense embeddings.
Focuses on keyword overlap and term frequency rather than latent semantic meaning.
"A massive wall of 50,000 light switches where only the specific switches labeled with the words in your sentence are flipped 'on'."
- Dense Embeddings(Counterpart)
- Hybrid Search(Implementation Strategy)
- Reciprocal Rank Fusion (RRF)(Scoring Method)
- Inverted Index(Underlying Data Structure)
Conceptual Overview
Sparse embeddings are high-dimensional vector representations where the vast majority of dimensions are zero, typically used in RAG to represent exact keyword importance and frequency (e.g., via BM25 or SPLADE). They provide a mechanism for precise lexical matching, acting as a technical counterbalance to the semantic 'fuzziness' of dense embeddings.
Disambiguation
Focuses on keyword overlap and term frequency rather than latent semantic meaning.
Visual Analog
A massive wall of 50,000 light switches where only the specific switches labeled with the words in your sentence are flipped 'on'.