Cross-Encoder Reranking

Cross-encoder reranking is one of the strongest second-stage techniques used to improve retrieval quality. Because the query and candidate document are processed jointly rather than separately, the model can capture more nuanced semantic interactions. Although computationally expensive, it yields significant quality gains when applied over a top-k candidate pool. It is a practical backbone of QA and semantic search systems.