Voyage AI has launched rerank-1, a state-of-the-art general-purpose and multilingual reranker that refines search results using cross-encoder transformers. This new tool outperforms Cohere's english-v3 on English datasets and multilingual-v3 on multilingual datasets. The reranker enhances the precision and relevance of search results, making it a valuable asset for improving information retrieval accuracy. It integrates seamlessly via an API call on top of any search methods. Additionally, Vectara has introduced the Multilingual Reranker_v1, available exclusively for Scale customers, which can be integrated seamlessly via their UI and API.
Really great work by @Voyage_AI_ A re-ranker based on a Cross-Encoder can substantially improve the final results for the user. The query and a possible document is passed simultaneously to transformer network, which then outputs a single score between 0 and 1 indicating how⦠https://t.co/bNAhKeFrwO
A cross-encoder reranker can significantly improve your search / retrieval accuracy and is incredibly easy to use β itβs just an API call on top of any search methods. Very impressed by our team at @Voyage_AI_ for the amazing work on this SOTA reranker! https://t.co/F2ZnwzahUE
ππ’ We are thrilled to launch rerank-1, our best general-purpose and multilingual reranker! It refines the ranking of your search results with cross-encoder transformers. It outperforms Cohere's english-v3 on English datasets and multilingual-v3 on multilingual datasets π. https://t.co/HnR1spwVCV
π What is Reranking and Why Do You Need It? Reranking is the process of refining search results to enhance precision and relevance. By applying advanced models, reranking ensures that the most pertinent documents are prioritized, boosting the overall effectiveness of retrieval.
Elevate your company's data-driven decision-making with our latest innovation: The Multilingual Reranker_v1 Available exclusively for Scale customers, integrate seamlessly via our UI and API. Check out our blog to transform your information retrieval. https://t.co/hSndJ31ovS