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arXiv · 2406.18038

MT2ST: Adaptive Multi-Task to Single-Task Learning

Dong Liu·Yanxuan Yu
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Abstract

Efficient machine learning (ML) has become increasingly important as models grow larger and data volumes expand. In this work, we address the trade-off between generalization in multi-task learning (MTL) and precision in single-task learning (STL) by introducing the Multi-Task to Single-Task (MT2ST) framework. MT2ST is designed to enhance training efficiency and accuracy in multi-modal tasks, showcasing its value as a practical application of efficient ML.

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Dong Liu, Yanxuan Yu. 2024-06-26. MT2ST: Adaptive Multi-Task to Single-Task Learning. https://arxiv.org/abs/2406.18038

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