late-interaction
A modeling paradigm in information retrieval that retains a separate embedding vector for each token of the query and the document, computing fine-grained similarity through operations such as MaxSim at retrieval time. Recall accuracy is typically better than single-vector dual-encoder models, but index size and scoring computation are larger.
Timeline (last 90 days)
pplx-embed-v2-late adopts a late-interaction architecture, retaining token-level representations and performing interaction computation at the retrieval stage.
The index size of late-interaction models is significantly larger than that of single-vector models, since each document requires storing hundreds of vectors, and the scoring stage also involves more computation, so practical systems often combine vector quantization (such as PLAID) for acceleration.
Late interaction is a modeling paradigm in information retrieval, popularized by the ColBERT line of work, which uses operations such as MaxSim to compute the sum of maximum similarities between query and document tokens as the relevance score.
When deploying a late-interaction retrieval scheme, note that the vector database must support multi-vector retrieval and that storage overhead is far higher than for single-vector indexes, so disk cost should be evaluated.
The late-interaction architecture retains multi-vector representations at the token or patch level, performing fine-grained matching between all sub-vectors of queries and documents at the retrieval stage.
The storage and computational overhead introduced by multi-vector representations is the core cost that the late-interaction approach must weigh against single-vector embedding solutions.
All Facts (6)
pplx-embed-v2-late adopts a late-interaction architecture, retaining token-level representations and performing interaction computation at the retrieval stage.
50%UnverifiedThe index size of late-interaction models is significantly larger than that of single-vector models, since each document requires storing hundreds of vectors, and the scoring stage also involves more computation, so practical systems often combine vector quantization (such as PLAID) for acceleration.
50%UnverifiedLate interaction is a modeling paradigm in information retrieval, popularized by the ColBERT line of work, which uses operations such as MaxSim to compute the sum of maximum similarities between query and document tokens as the relevance score.
50%UnverifiedWhen deploying a late-interaction retrieval scheme, note that the vector database must support multi-vector retrieval and that storage overhead is far higher than for single-vector indexes, so disk cost should be evaluated.
50%UnverifiedThe late-interaction architecture retains multi-vector representations at the token or patch level, performing fine-grained matching between all sub-vectors of queries and documents at the retrieval stage.
50%UnverifiedThe storage and computational overhead introduced by multi-vector representations is the core cost that the late-interaction approach must weigh against single-vector embedding solutions.
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