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Found 2 papers, 1 papers with code
Data Efficient and Weakly Supervised Computational Pathology on Whole Slide Images
CLAM is a general-purpose and adaptable method that can be used for a variety of different computational pathology tasks in both clinical and research settings.
Scaling Federated Learning for Fine-tuning of Large Language Models
We perform an extensive sweep over the number of clients, ranging up to 32, to evaluate the impact of distributed compute on task performance in the federated averaging setting.
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