A multi-strategy interrogation method with auxiliary expert assessment reduces expected calibration error by 40% on average across three medical VQA datasets for MLLMs.
arXiv preprint (2022), https://arxiv.org/abs/2210.12265, arXiv:2210.12265
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Confidence Calibration for Multimodal LLMs: An Empirical Study through Medical VQA
A multi-strategy interrogation method with auxiliary expert assessment reduces expected calibration error by 40% on average across three medical VQA datasets for MLLMs.