“Hallucinations” is a term coined to describe when LLM models produce what?

In the context of LLMs, “hallucinations” refer to outputs that sound plausible and correct but are factually incorrect or fabricated, as emphasized in NVIDIA’s Generative AI and LLMs course. This occurs when models generate responses based on patterns in training data without grounding in factual knowledge, leading to misleading or invented information. Option A is incorrect, as hallucinations are not about similarity to input data but about factual inaccuracies. Option B is wrong, as hallucinations typically refer to text, not image generation. Option D is inaccurate, as hallucinations are grammatically coherent but factually wrong. The course states: “Hallucinations in LLMs occur when models produce correct-sounding but factually incorrect outputs, posing challenges for ensuring trustworthy AI.”