AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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Temporal Domain Generalization (TDG) has emerged to address real-world streaming data with distribution shifts over time. However, existing methods are either prone to overfitting to domain-specific noise in the data space or become overly complex and less interpretable in the parameter space. To bridge these gaps, we...
The proposed QiYao-M is a role-aware multimodal TSFM that models the two types of modalities separately, including endogenous and exogenous modalities, and introduces Endo-Modality Proxy Training to train this retrieval module without exogenous multimodal pretraining data.
ST-EVO is proposed, which supports dialogue-wise communication scheduling with a compact yet powerful flow-matching based Scheduler to make precise Spatio-Temporal scheduling, and can also perceive the uncertainty of MAS, and possesses self-feedback ability to learn from accumulated experience.
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