xhLiu/

MM_eval

Calibrated Multimodal Representation Learning with Missing Modalities

Multimodal representation learning under partial-modality settings

CalMRL is a multimodal representation learning framework designed for alignment calibration when some modalities are missing. CalMRL combines two complementary goals:

Cross-modal alignment for robust shared representations Missing-modality calibration through posterior inference and learned generative parameters… See the full description on the dataset page: https://huggingface.co/datasets/xhLiu/MM_eval.