Imagine a large language model tasked with generating a summary of a historical event. Despite producing fluent and grammatical correct text,the summary contains several factual inaccuracies not present in the original historical records.In the context of Large Language Models and Reinforcement Learning with Human Feedback, this phenomenon is best described as:

Bias amplification
Reward hacking
Hallucination
Overfitting
Verified Answer
Correct Option - c

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