SELF-RAG: Improving the Factual Accuracy of Large Language Models through Self-Reflection

In recent years, artificial intelligence researchers have made astounding progress developing large language models that can generate remarkably human-like text. Models like GPT-3 and PaLM with billions or trillions of parameters display impressive versatility in language tasks. However, a major limitation persists - these models still frequently generate factual inaccuracies

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