A cross-encoder processes the query and document together through a single transformer pass, allowing full cross-attention between them. This produces highly accurate relevance scores but is too slow for searching large collections since every document must be scored at query time. Cross-encoders are typically used as rerankers: a fast bi-encoder retrieves candidates, and the cross-encoder re-scores the top results.