
You are working with a language model that sometimes produces confident but incorrect answers. Your team wants a practical way to reduce those hallucinations without retraining the model. You have access to a small set of high-quality examples and can change the prompt format.
How do you handle hallucination in an LLM, and what specific few-shot techniques would you apply to mitigate it?