To address RAG retrieval failures caused by semantic fragmentation , this study introduces a "Context Extension + Two-Round Re-ranking" strategy. By shifting from isolated segment evaluation to a human-like "scanning" process—locating key chunks, dynamically expanding to adjacent context, and performing a final re-ranking—the system restores semantic coherence. Empirical results confirm that this method significantly improves retrieval completeness and accuracy, offering a high-precision solution for complex, long-document RAG applications without requiring complex re-chunking.

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