Knowledge Hallucination

Knowledge hallucination, the generation of factually incorrect information by AI models, particularly large language models (LLMs), is a significant challenge hindering their reliable application. Current research focuses on understanding the root causes, such as data imbalance and over-generalization, and developing methods to detect and mitigate hallucinations, including techniques that leverage internal model states and self-contrastive decoding. These efforts aim to improve the trustworthiness and accuracy of AI systems across diverse applications, from question answering and image captioning to robot navigation, where factual accuracy is paramount.