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https://arxiv.org/pdf/2607.26188v1
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Matching-Driven Deep Reinforcement Learning for Energy-Efficient

https://arxiv.org/html/2407.13076v1
Index Terms: LoRa, multigateway, system energy efficiency, matching-based, multiagent deep reinforcement learning

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https://arxiv.org/src/2211.10435
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https://arxiv.org/src/2407.17789
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Optimizing Age of Information in Vehicular Edge Computing with Federated

https://arxiv.org/html/2407.02342v1
com/qiongwu86/Optimizing-AoI-in-VEC-with-Federated-Graph-Neural-Network-Multi-Agent-Reinforcement-Learnin

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https://arxiv.org/pdf/2402.03300
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https://arxiv.org/pdf/2608.03118
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https://arxiv.org/src/2006.03720
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https://arxiv.org/pdf/2607.26405v1
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https://arxiv.org/src/2405.20232
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https://arxiv.org/src/2005.13905
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https://arxiv.org/pdf/2608.04008
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https://arxiv.org/pdf/2407.02402
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https://arxiv.org/pdf/2006.02318
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https://arxiv.org/src/2006.02893
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https://arxiv.org/pdf/2607.27070v1
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https://arxiv.org/pdf/2608.01934
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https://arxiv.org/pdf/2407.02510
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https://arxiv.org/pdf/2608.02976
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https://arxiv.org/pdf/2608.02122
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https://arxiv.org/pdf/2608.03095
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https://arxiv.org/pdf/2006.15704
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https://arxiv.org/src/2608.03883
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https://arxiv.org/src/2006.02759
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https://arxiv.org/pdf/2608.03437
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https://arxiv.org/pdf/2607.27188v1
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https://arxiv.org/src/2006.02230
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https://arxiv.org/src/2006.03271
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https://arxiv.org/pdf/2407.00225
-scale, Independent and Comprehensive study of the power of LLMs for test case generationWendkûuni C. OuédraogoKader KaboréYinghua LiHaoye TianAnil KoyuncuJacques KleinDavid LoTegawendé F. Bissyandéhttp://creativecommons.org/licenses

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https://arxiv.org/pdf/2608.03883
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