Weaviate: Using Cross-Encoders for Multistage Vector Search Reranking

AI Impact Summary

Combining Bi-Encoders and Cross-Encoders offers a tiered approach to semantic search, addressing the inherent trade-offs between speed and accuracy. Initial retrieval with Bi-Encoders rapidly narrows down the search space, followed by a Cross-Encoder’s higher-fidelity ranking to refine results. This staged process leverages the strengths of both models, enabling efficient and accurate search on large datasets, particularly useful for applications like Weaviate’s vector search capabilities.