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KG-CQR is a novel framework that enhances the retrieval phase in RAG systems by enriching complex input queries with contextual representations from a corpus-centric KG. It comprises subgraph extraction, subgraph completion, and contextual generation modules, ultimately improving the context provided to LLMs during inference for tasks like question answering.
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