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Multi-Hop Retrieval

A retrieval strategy where an AI agent iteratively executes multiple search steps, using the insights from one step to formulate the query for the next, in order to answer complex questions requiring synthesized information from disparate sources. While it enables the resolution of complex 'bridging' queries, it introduces architectural trade-offs such as significantly increased latency and the risk of compounding errors/hallucinations across intermediate hops.

Definition

A retrieval strategy where an AI agent iteratively executes multiple search steps, using the insights from one step to formulate the query for the next, in order to answer complex questions requiring synthesized information from disparate sources. While it enables the resolution of complex 'bridging' queries, it introduces architectural trade-offs such as significantly increased latency and the risk of compounding errors/hallucinations across intermediate hops.

Disambiguation

Sequential context-building vs. single-shot vector search.

Visual Metaphor

"A detective following a trail of breadcrumbs through different rooms to find a final piece of evidence."

Key Tools
LangChain (Self-Query)LlamaIndex (SubQuestionQueryEngine)DSPyNeo4jGraphRAG
Related Connections

Conceptual Overview

A retrieval strategy where an AI agent iteratively executes multiple search steps, using the insights from one step to formulate the query for the next, in order to answer complex questions requiring synthesized information from disparate sources. While it enables the resolution of complex 'bridging' queries, it introduces architectural trade-offs such as significantly increased latency and the risk of compounding errors/hallucinations across intermediate hops.

Disambiguation

Sequential context-building vs. single-shot vector search.

Visual Analog

A detective following a trail of breadcrumbs through different rooms to find a final piece of evidence.

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