<ul><li>Transition from 5G to 6G is driving demand for machine learning (ML) in mobile networking and communications for advanced services.</li><li>The rise of Internet-of-Things (IoT) devices has accelerated the development of TinyML and resource-efficient ML, while LargeML demands significant computing resources.</li><li>Integration of TinyML and LargeML is seen as a promising approach for efficient resource management and seamless connectivity.</li><li>Challenges like performance optimization, deployment strategies, resource management, and security need to be addressed for successful integration in future wireless networks.</li></ul>

Integration of TinyML and LargeML: A Survey of 6G and Beyond

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