What term is used to describe instances when LLMs invent information, especially in quotes or details?

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The term "hallucinations" is used to describe instances when large language models (LLMs) generate or "invent" information that is not based on their training data or actual facts. This phenomenon occurs because these models are designed to predict and produce text based on patterns they learned during training, rather than relying on a database of true statements. As a result, they can sometimes create plausible-sounding content that lacks factual accuracy, leading to the occurrence of fabricated quotes, misleading details, or entirely fictitious information.

This behavior is particularly important to understand in the context of generative AI, as it highlights the need for users to critically evaluate the outputs these models produce. Recognizing the risk of hallucinations is essential for fostering responsible AI usage and ensuring that generated information is cross-verified against reliable sources.

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