WeiHongLee/Awesome-Multi-Task-Learning
An up-to-date list of works on Multi-Task Learning
This resource helps machine learning researchers and practitioners understand the latest advancements in Multi-Task Learning (MTL). It provides a curated collection of research papers, surveys, benchmarks, and code implementations, allowing you to explore different approaches and their applications. You'll find materials covering various real-world tasks like urban scene understanding, object detection, and image classification, aiding in the development of more efficient and robust AI models.
376 stars.
Use this if you are a machine learning researcher or practitioner looking for a comprehensive and up-to-date overview of Multi-Task Learning, including key research, datasets, and practical code examples.
Not ideal if you are looking for a plug-and-play software tool for immediate implementation without understanding the underlying research.
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Last pushed
Mar 02, 2026
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