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Found 4 papers, 3 papers with code
Backdoor Attack on Unpaired Medical Image-Text Foundation Models: A Pilot Study on MedCLIP
Notably, MedCLIP, a vision-language contrastive learning-based medical FM, has been designed using unpaired image-text training.
Scalable Data Point Valuation in Decentralized Learning
The valuation of data points through DDVal allows to also draw hierarchical conclusions on the contribution of institutions, and we empirically show that the accuracy of DDVal in estimating institutional contributions is higher than existing Shapley value approximation methods for federated learning.
Federated Virtual Learning on Heterogeneous Data with Local-global Distillation
To address this, we propose a new method, called Federated Virtual Learning on Heterogeneous Data with Local-Global Distillation (FedLGD), which trains FL using a smaller synthetic dataset (referred as virtual data) created through a combination of local and global dataset distillation.
Efficient Medical Image Assessment via Self-supervised Learning
Existing data assessment methods commonly require knowing the labels in advance, which are not feasible to achieve our goal of 'knowing which data to label.'
