Leading AI models like GPT and Gemini frequently provide correct answers but often cite incorrect sources, a phenomenon termed 'attribution hallucination.' This issue poses risks in regulated sectors such as law and medicine, prompting researchers to develop a new benchmark, CiteVQA, to systematically test for this problem.