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Griffith University, N|y^i鈭抷i|,\mathrm{MAE}=\frac{1}{N}\sum_{i=1}^{N}|\hat{y}_{i}-y_{i}|, (15) where y^i\hat{y}_{i} denotes the predicted accuracy for dataset ii, and yiy_{i} is the corresponding true accuracy. A lower MAE indicates a more reliable and stable evaluator. We report EM/EX for model accuracy and MAE for evaluator accuracy across all transfers to measure generalization. Base Models. Shift descriptors are collected from five representative Text
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Unleashing the full reasoning potential of VLMs, AgentM3D adaptively scales test-time reasoning paths to achieve state-of-the-art zero-shot multi-modal misinformation detection.
