Ranking Models for Better Search — Cross Encoders, Metadata Rankers, Score Rankers

AI Impact Summary

OpenAI is introducing ranking models to improve search quality by leveraging the ability of large language models to assess relevance. These models, categorized as Cross Encoders, Metadata Rankers, and Score Rankers, operate by taking a query and candidate document as input and predicting relevance. This approach contrasts with traditional vector and lexical search methods, offering a potentially faster and more nuanced way to re-rank search results, particularly when combined with hybrid search strategies like Weaviate.