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KG-Rank is an augmented LLM framework that integrates a medical Knowledge Graph with novel ranking and re-ranking techniques. It identifies entities, retrieves relevant KG triples, and applies methods like Similarity Ranking, Answer Expansion Ranking, and MMR Ranking, followed by MedCPT-based re-ranking to provide relevant and precise information to LLMs during inference. The primary goal is to improve the factual consistency and reliability of LLM-generated long-form answers in medical Question Answering.
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