The Census of Hallucinations

The Census of Hallucinations is a study that systematically identifies and categorizes false or misleading responses generated by AI language models. It aims to understand how often and in what ways these models "hallucinate"—producing information that is incorrect, unsubstantiated, or fictional—despite appearing confident. By analyzing these patterns, researchers can improve AI accuracy and develop better methods to prevent or reduce such inaccuracies, ultimately making AI responses more reliable and trustworthy for users.