Voyage rerank-1: Cutting-Edge General Purpose and Multilingual Reranker

Voyage introduces rerank-1, an advanced reranker that surpasses previous models like bge-reranker-v2-m3 and Cohere’s rerank-english-v3 and rerank-multilingual-v3 across 37 domain-specific and 50 multilingual datasets, including languages such as French, German, Japanese, Korean, and Spanish. This new model offers an 8k context length, doubling that of rerank-lite-1 and Cohere’s rerank-english-v3, enhancing the relevancy of existing search systems. The evaluation of rerank-1 involved a wide array of datasets in fields such as technical documentation, code, law, finance, medicine, and conversations, demonstrating its superior performance in retrieving relevant documents using both lexical and embedding-based search methods. The model is particularly effective in improving retrieval quality across various domains and languages, showing consistent superiority over other rerankers in tests and enhancing retrieval quality in cases where first-stage search methods alone were insufficient. Voyage encourages users to integrate rerank-1 into their existing search systems to boost retrieval quality and invites interest in their upcoming domain-specific and fine-tuning embeddings.