AI engineering glossary · RAG vector search
What is SPLADE (learned sparse retrieval)?
Learned sparse retrieval (also called SPLADE): Retrieval where a neural model assigns weights to vocabulary terms, including expansion terms not in the text, producing a sparse vector usable with an inverted index. It blends keyword-style exactness with some semantic matching.
Learned sparse retrieval: an example
SPLADE-style models add related words such as 'automobile' to a passage about 'car' with learned weights.
Related terms
More RAG vector search terms
- LLM-as-judge
- Locality-sensitive hashing
- M parameter
- Maximal marginal relevance
- Metadata filtering
- Multi-hop retrieval
- Multi-query retrieval
- Multi-tenancy
Where you learn it
Learned sparse retrieval is part of the AI Engineering Program, which teaches it with notes, a hands-on lab and an exam. The first lesson is free.