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Auxiliary Learning

Auxiliary learning aims to find or design auxiliary tasks which can improve the performance on one or some primary tasks.

( Image credit: Self-Supervised Generalisation with Meta Auxiliary Learning )

Papers

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Showing 61–70 of 100 papers

TitleStatusHype
Large Language Models for Compiler Optimization—0
Learning Multiple Representations with Inconsistency-Guided Detail Regularization for Mask-Guided Matting—0
Learning Representation for Multitask learning through Self Supervised Auxiliary learning—0
Learning to Generalize One Sample at a Time with Self-Supervision—0
Leveraging Synthetic Discourse Data via Multi-task Learning for Implicit Discourse Relation Recognition—0
Leveraging Visual Question Answering to Improve Text-to-Image Synthesis—0
Light Field Image Quality Assessment With Auxiliary Learning Based on Depthwise and Anglewise Separable Convolutions—0
LitCall: Learning Implicit Topology for CNN-based Aortic Landmark Localization—0
Meta Auxiliary Labels with Constituent-based Transformer for Aspect-based Sentiment Analysis—0
Meta-Auxiliary Learning for Adaptive Human Pose Prediction—0
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