Hallucination elimination and grounding

Language models confidently generate plausible but factually incorrect statements, a phenomenon known as hallucination or confabulation. Retrieval-augmented generation (RAG) reduces but does not eliminate the problem, as models can ignore or misrepresent retrieved context. Reliable attribution, calibrated uncertainty estimation, and detection of knowledge conflicts between parametric and contextual knowledge are all active research areas. Eliminating hallucination while preserving the generative fluency and creativity of language models is a fundamental tension.