Unverified50% confidenceTradeoffExact time
Multi-hop queries need to traverse multiple information nodes in a step-by-step manner, and vector retrieval is ill-suited for such scenarios due to its lack of a relational dimension.
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Long-term
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9/10/2026
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Related Claims
UnverifiedRAG suffers from a scattered-answer problem because the current retrieval approach scores relevance between a query and individual chunks, making it difficult to guarantee that multiple complementary chunks are retrieved simultaneously.79% similarUnverifiedVector retrieval is inherently weak at multi-hop reasoning; when an answer requires synthesizing scattered information fragments from multiple documents, pure similarity ranking often fails to retrieve all necessary context.78% similarUnverifiedGlobal queries can answer inductive questions requiring a macro perspective (such as the main themes across an entire document set), a scenario that pure vector retrieval is almost incapable of handling.77% similarUnverified从事件监听打断点并沿调用栈逐层追溯，比盲目全局搜索效率更高且不易遗漏中间数据转换环节74% similarUnverifiedORMs often fall short when handling complex queries, batch operations, and highly optimized data access paths, and may produce the N+1 query problem.74% similar
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