Hallucination Benchmark in Medical Visual Question Answering
2024-01-11Code Available0· sign in to hype
Jinge Wu, Yunsoo Kim, Honghan Wu
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- github.com/knowlab/halt-medvqaOfficialIn paperpytorch★ 9
Abstract
The recent success of large language and vision models (LLVMs) 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.