Hallucination Benchmark in Medical Visual Question Answering
CoRR(2024)
摘要
The recent success of large language and vision models on vision question
answering (VQA), particularly their applications in medicine (Med-VQA), has
shown a great potential of realizing effective visual assistants for
healthcare. However, these models are not extensively tested on the
hallucination phenomenon in clinical settings. Here, we created a hallucination
benchmark of medical images paired with question-answer sets and conducted a
comprehensive evaluation of the state-of-the-art models. The study provides an
in-depth analysis of current models limitations and reveals the effectiveness
of various prompting strategies.
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