Late Interaction Retrieval
Overview
Late interaction retrieval represents queries and documents as sets of contextual token vectors, then compares them during search so that a relevant phrase or passage can match without requiring whole-text embeddings to align. ColBERT-style MaxSim is a common scoring method, paired with techniques such as approximate nearest-neighbor search, quantization, token selection, and vector compression to control indexing and query costs. The approach is used in text search and increasingly in visual documents, video, biomedical linking, and long-term memory, with evaluations including BEIR, MS MARCO, and ViDoRe. A central challenge is balancing fine-grained matching quality against storage and latency, while managing sensitivity to document length and ensuring performance transfers to longer or unfamiliar queries.
Latest papers
28 papers5 papers in the last four weeks, down 17% on the four weeks before. 0.0% of all new papers.