Resilient Vision-Tabular Multimodal Learning under Modality Missingness

ArXi:2605.12031v1 Announce Type: new Multimodal deep learning has shown strong potential in medical applications by integrating heterogeneous data sources such as medical images and structured clinical variables. However, most existing approaches implicitly assume complete modality availability, an assumption that rarely holds in real-world clinical settings where entire modalities and individual features are frequently missing.