Enhancing Robustness of Multimodal Learning Models to Handle Missing Modalities via Parameter-Efficient Adaptation

Multimodal learning models can be made robust to missing modalities through a simple and parameter-efficient adaptation procedure that modulates the intermediate features of available modalities to compensate for the missing ones.