Late Interaction and ColBERT: How Multi-Vector Embeddings and the MaxSim Operator Transform Neural Retrieval
Information retrieval systems have long wrestled with a fundamental tension between computational efficiency and semantic expressiveness. Traditional dense bi-encoders like DPR compress an entire passage into a single dense vector, allowing sub-linear approximate nearest neighbor (ANN) search over millions of documents. However, forcing multi-sentence passages into a single vector representation creates an information bottleneck that discards fine-grained token-level nuances, entities, and keywo
1 min