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Contextual Compression and Reranking ColBERT or Cross Encoders

Contextual compression uses ColBERT or cross-encoders to rerank retrieved text, reduce context noise, lower token use, and improve RAG precision.

In the full article

  1. How does contextual compression work in a RAG pipeline?
  2. How do ColBERT and cross-encoders differ?
  3. Why does context pruning improve answer quality and cost?
  4. When should teams use a multi-stage retrieval pipeline?
  5. Key takeaways
  6. How Hyperlake helps
  7. Frequently asked questions

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