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Understanding Reciprocal Rank Fusion (RRF) in Retrieval-Augmented Systems

In our last discussion, we explored how Retrieval-Augmented Generation (RAG) enhances large language models (LLMs) by fetching external information to improve their responses. Today, let's dive deeper into a key retrieval technique used inside RAG systems: Reciprocal Rank Fusion (RRF). ✨ What is Reciprocal Rank Fusion (RRF)? Reciprocal Rank Fusion is a simple yet powerful algorithm used to combine search results from multiple queries. Instead of depending on just a single query to retrieve documents, RRF: Fans out multiple subqueries Retrieves results separately for each Merges them so that higher-ranked results are prioritized across the different searches

Apr 26, 2025 - 19:47
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Understanding Reciprocal Rank Fusion (RRF) in Retrieval-Augmented Systems

In our last discussion, we explored how Retrieval-Augmented Generation (RAG) enhances large language models (LLMs) by fetching external information to improve their responses.

Today, let's dive deeper into a key retrieval technique used inside RAG systems: Reciprocal Rank Fusion (RRF).

✨ What is Reciprocal Rank Fusion (RRF)?

Reciprocal Rank Fusion is a simple yet powerful algorithm used to combine search results from multiple queries.

Instead of depending on just a single query to retrieve documents, RRF:

  • Fans out multiple subqueries
  • Retrieves results separately for each
  • Merges them so that higher-ranked results are prioritized across the different searches

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