Different Roles for Different Models: LLMs and Reinforcement Learning
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Large language models are hampered by hallucination, the generation of incorrect or nonsensical text that is semantically or syntactically plausible. This is a serious problem that limits their usefulness, especially to automate complex, error-prone tasks at scale. Some experts believe that reinforcement learning with human feedback can eliminate hallucinations. Others argue that a more fundamental flaw in large language models is at work.