GAUGE: Granularity-Adaptive Counterfactual Gating of Evidence for Incomplete Multimodal Classification
GAUGE is proposed, a lightweight counterfactual gating framework for incomplete multimodal classification that outperforms strong baselines across diverse incomplete-input settings and is established as a principled and scalable framework for fine-grained evidence control under modality incompleteness.