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%20enhances%20large%20language%20models%20(LLMs)%20by%20incorporating%20additional%20information%20from%20retrieval.%20However%2C%20studies%20have%20shown%20that%20LLMs%20still%20face%20challenges%20in%20effectively%20using%20the%20retrieved%20information%2C%20even%20ignoring%20it%20or%20being%20misled%20by%20it.%20The%20key%20reason%20is%20that%20the%20training%20of%20LLMs%20does%20not%20clearly%20make%20LLMs%20learn%20how%20to%20utilize%20input%20retrieved%20texts%20with%20varied%20quality.%20In%20this%20paper%2C%20we%20propose%20a%20novel%20perspective%20that%20considers%20the%20role%20of%20LLMs%20in%20RAG%20as%20%60%60Information%20Refiner''%2C%20which%20means%20that%20regardless%20of%20correctness%2C%20completeness%2C%20or%20usefulness%20of%20retrieved%20texts%2C%20LLMs%20can%20consistently%20integrate%20knowledge%20within%20the%20retrieved%20texts%20and%20model%20parameters%20to%20generate%20the%20texts%20that%20are%20more%20concise%2C%20accurate%2C%20and%20complete%20than%20the%20retrieved%20texts.%20To%20this%20end%2C%20we%20propose%20an%20information%20refinement%20training%20method%20named%20InFO-RAG%20that%20optimizes%20LLMs%20for%20RAG%20in%20an%20unsupervised%20manner.%20InFO-RAG%20is%20low-cost%20and%20general%20across%20various%20tasks.%20Extensive%20experiments%20on%20zero-shot%20prediction%20of%2011%20datasets%20in%20diverse%20tasks%20including%20Question%20Answering%2C%20Slot-Filling%2C%20Language%20Modeling%2C%20Dialogue%2C%20and%20Code%20Generation%20show%20that%20InFO-RAG%20improves%20the%20performance%20of%20LLaMA2%20by%20an%20average%20of%209.39%25%20relative%20points.%20InFO-RAG%20also%20shows%20advantages%20in%20in-context%20learning%20and%20robustness%20of%20RAG.)
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