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Found 5 papers, 1 papers with code
Task Indicating Transformer for Task-conditional Dense Predictions
The task-conditional model is a distinctive stream for efficient multi-task learning.
YOLO-MED : Multi-Task Interaction Network for Biomedical Images
Object detection and semantic segmentation are pivotal components in biomedical image analysis.
Federated Multi-Task Learning on Non-IID Data Silos: An Experimental Study
The innovative Federated Multi-Task Learning (FMTL) approach consolidates the benefits of Federated Learning (FL) and Multi-Task Learning (MTL), enabling collaborative model training on multi-task learning datasets.
FedHCA$^2$: Towards Hetero-Client Federated Multi-Task Learning
Moreover, we employ learnable Hyper Aggregation Weights for each client to customize personalized parameter updates.
Prompt Guided Transformer for Multi-Task Dense Prediction
Task-conditional architecture offers advantage in parameter efficiency but falls short in performance compared to state-of-the-art multi-decoder methods.
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