Cross-Encoder Reranking

Neural reranking models for improved relevance.

Rerank Results

Rerank search results with cross-encoder:

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-- Rerank search results
SELECT idx, score FROM rerank_cross_encoder(
    'What is machine learning?',           -- query
    ARRAY[                                  -- candidate texts
        'Neural networks tutorial',
        'Deep learning basics',
        'AI history'
    ],
    'ms-marco-MiniLM-L-6-v2',              -- model name
    3                                       -- top K
);

Batch Reranking

Rerank multiple queries:

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-- Batch reranking
SELECT query_id, idx, score
FROM rerank_cross_encoder_batch(
    ARRAY['query 1', 'query 2'],
    ARRAY[
        ARRAY['doc 1', 'doc 2'],
        ARRAY['doc 3', 'doc 4']
    ],
    'model_name',
    5
);

Learn More

For detailed documentation on cross-encoder models, model selection, fine-tuning, and performance optimization, visit:

Cross-Encoder Documentation

Related Topics

• LLM Reranking - LLM-powered reranking
• Ensemble - Combine reranking strategies