IEEE

Tackling Modality-Heterogeneous Client Drift Holistically for Heterogeneous Multimodal Federated Learning

Abstract: Multimodal Federated Learning (MFL) has emerged as a collaborative paradigm for training models across decentralized devices, harnessing various data modalities to facilitate effective ...
GitHub

Multimodal Learning Under Imperfect Data Conditions: A Survey

Authors: Muhamamd Irzam Liaqat, Qaiser Abbas, Shah Nawaz, Muhammad Zaigham Zaheer, Marta Moscati, Yufang Hou, Muhammad Haris Khan, Salman Khan, Elisabeth Andre, Markus Schedl Fig 1: Abstract Overview ...
GitHub

Jian-Lang/awesome-modality-missing-learning

Deep Multimodal Learning with Missing Modality: A Survey TMLR 2026 Paper N/A Multimodal Learning Under Imperfect Data Conditions: A Survey arxiv 2026 Paper N/A Multimodal fusion on low-quality data: A ...
IEEE

Agnostic-Specific Modality Learning for Cancer Survival Prediction From Multiple Data

Abstract: Cancer is a pressing public health problem and one of the main causes of mortality worldwide. The development of advanced computational methods for predicting cancer survival is pivotal in ...