Supervised finetuning (SFT) datasets, which are created by human annotators, can introduce factual errors into large language models because human annotators make mistakes, have knowledge gaps, and may produce authoritative-sounding text on topics outside their expertise.

Authors

• Person: M. Brenndoerfer Organization: mbrenndoerfer.com
  Hallucination Causes: Why Language Models Fabricate Facts

Sources

• Hallucination Causes: Why Language Models Fabricate Facts mbrenndoerfer.com M. Brenndoerfer · mbrenndoerfer.com via serper

Referenced by nodes (2)

• Large Language Models concept
• supervised fine-tuning concept