Abstract: Federated learning (FL) is recognized as a pivotal paradigm for 6G, offering decentralized model training without compromising data privacy. Recent works have proposed deploying FL in ...
Abstract: This paper proposes a fair allocation approach for dynamic operating envelope-integrated local energy trading with the intention of offering financial benefits to electricity customers ...
Our research paper, "The Kubernetes Network Driver Model: A Composable Architecture for High-Performance Networking", provides a deep dive into the DraNet model and its impact. The DraNet driver ...
A lightweight framework that gives language models (LMs) a persistent, evolving memory during inference time. Dynamic Cheatsheet (DC) endows black-box language models with the ability to store and ...
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