LanceDB supports a variety of reranking models to improve search result quality. Choose the model that best fits your use case and performance requirements.
Available Reranking Models
| Model | Use Case |
|---|---|
| Cohere Reranker | Production applications requiring high accuracy |
| CrossEncoder | Semantic similarity and relevance scoring |
| ColBERT | Fast and accurate reranking with context |
| OpenAI Reranker | OpenAI ecosystem integration |
| VoyageAI Reranker | High-performance semantic search |
| Jina Reranker | Jina ecosystem integration |
| AnswerDotAI Reranker | Specialized for Q&A and conversational search |
| Linear Combination | Ensemble methods for improved performance |
| Reciprocal Rank Fusion (RRF) | Robust ensemble ranking without training |
| Evaluation | Model selection and optimization |