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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/2006.02318
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https://arxiv.org/pdf/2607.27188v1
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https://arxiv.org/pdf/2608.03883
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1 Introduction

https://arxiv.org/html/2407.16741v3
com/All-Hands-AI/OpenHands Slack http://bit

Global coal trade is resilient to maritime chokepoints

https://arxiv.org/html/2608.00328v2
The exception is a restriction to maritime traffic in the South and East China Sea, which could raise costs by 10 $/t for China, whilst reducing costs for other importers in the region by similar levels

Multi-agent Off-policy Actor-Critic Reinforcement Learning for Partially

https://arxiv.org/html/2407.04974v1
Unlike many existing dec-POMDP-based RL approaches, the proposed algorithm is suitable for model-free multi-agent reinforcement learning as it does not require knowledge of a transition model

Automatic Patient-Specific Microwave Ablation Planning Accelerated by a

https://arxiv.org/html/2608.03086v1
Physics-Guided Deep Learning Model Report GitHub Issue × Title: Content selection saved. Describe the issue below: Description: Submit without GitHub Submit in GitHub arXiv is now an independent nonprofit! Learn more × Back to arXiv

Efficient Multilingual Neural Machine Translation via Corpus-Driven

https://arxiv.org/html/2608.03480v1
com Arabic Institute for Translation, Algiers, Algeria CERIST, Algeria Nasredine Semmar CEA LIST, Paris-Saclay, France Hassina Aliane CERIST, Algeria Abstract The adoption of large pre-trained multilingual models for neural machine translation (MNMT) faces a major challenge: excessive memory and computational

Can Large Language Models Execute Parent Orders?

https://arxiv.org/html/2607.28410v1
com/zaneopen/PACE 1 Introduction Reducing execution costs is a central objective for financial institutions (Bertsimas and Lo 1998)

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https://arxiv.org/pdf/2608.02817
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https://arxiv.org/pdf/2005.14165
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https://arxiv.org/pdf/2608.02758
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https://arxiv.org/src/2407.17789
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https://arxiv.org/pdf/2608.03118
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https://arxiv.org/src/2405.20232
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https://arxiv.org/pdf/2402.03300
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https://arxiv.org/src/2006.02893
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https://arxiv.org/src/2006.03271
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https://arxiv.org/pdf/2608.03421
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https://arxiv.org/pdf/2608.02851v1
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https://arxiv.org/pdf/2006.00342
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https://arxiv.org/pdf/2211.01910
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https://arxiv.org/src/2303.12712
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https://arxiv.org/pdf/2006.03178
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https://arxiv.org/src/2006.01048
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https://arxiv.org/pdf/2303.12712v5
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https://arxiv.org/src/2006.02924
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https://arxiv.org/pdf/2608.02935
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https://arxiv.org/src/2104.08691
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