Revealing Epistemic Uncertainty in MLLMs via Causal-Invariant Masking
Multimodal Large Language Models (MLLMs) suffer from hallucinations, creating a critical need for Uncertainty Quantification (UQ) to ensure reliable deployment. However, existing approaches struggle to detect uncertainty caused by superficial associations, especially when the query-relevant signal is weak. We mainly at...
Hao-Yang Luo, Lin-Wei Tao, Jie Gui et al.
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