Adding task-supervised auxiliary modules to shared layers during training improves hard-parameter-sharing multi-task learning on segmentation, depth, and surface normal prediction, with no inference-time overhead.
Multi-task learning with multi-view attention for answer selection and knowledge base question answering
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Auxiliary Learning for Deep Multi-task Learning
Adding task-supervised auxiliary modules to shared layers during training improves hard-parameter-sharing multi-task learning on segmentation, depth, and surface normal prediction, with no inference-time overhead.