1 citations · 1 across the 3 of their papers we have counts for
4 papers
Self-Explainable Multi-Label Graph Neural Network for Correlated Evidence Attribution
Yingqi Feng, Yufei Tang, Min Shi +1
Multi-label graph learning intends to capture the intrinsic complexity of real-world applications, where one sample is often related to multiple groups or consists of multiple obje…
MultiFair: Multimodal Balanced Fairness-Aware Medical Classification with Dual-Level Gradient Modulation
Md Zubair, Hao Zheng, Grayson W. Armstrong +4
Medical decision systems increasingly rely on data from multiple sources to ensure reliable and unbiased diagnosis. However, existing multimodal learning models fail to achieve thi…
Combining Knowledge Graph and LLMs for Enhanced Zero-shot Visual Question Answering
Qian Tao, Xiaoyang Fan, Yong Xu +2
Zero-shot visual question answering (ZS-VQA), an emerged critical research area, intends to answer visual questions without providing training samples. Existing research in ZS-VQA…
TransFair: Transferring Fairness from Ocular Disease Classification to Progression Prediction
Leila Gheisi, Henry Chu, Raju Gottumukkala +4
The use of artificial intelligence (AI) in automated disease classification significantly reduces healthcare costs and improves the accessibility of services. However, this transfo…