ColBERT and Late Interaction at Scale: Why Multi-Vector Retrieval Strains Production Memory
In modern neural information retrieval, few architectural concepts have generated as much excitement as Late Interaction, pioneered by Omar Khattab and Matei Zaharia in the ColBERT series. On paper, ColBERT represents an ideal mathematical compromise. It delivers retrieval quality approaching a full cross-encoder while retaining the precomputable index structure of a bi-encoder. On out-of-domain benchmarks like BEIR, ColBERT routinely outperforms dense single-vector models by 5 to 10 points in nDCG@10. ...