A type of encoder that jointly processes query-document pairs to determine relevance.
More about Cross-Encoder
Cross-Encoders take a query and a document as input and process them together through a single model to calculate relevance. Unlike bi-encoders, which generate embeddings independently, cross-encoders allow for finer-grained relevance scoring by considering the interaction between query and document.
Cross-encoders are often used in tasks requiring high accuracy, such as re-ranking candidates retrieved by dense retrieval or hybrid search.
