AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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This work introduces a new regime, Time-Series Interaction: a model continuously perceives incoming time-series observations and user intent, autonomously decides when to remain silent or respond, and continues processing new observations during response generation.
A novel framework of temporal memory-aware Online Test-Time Adaptation on Dynamic Graphs, named DGOTTA, to effectively adapt well-trained DGNNs during test time and significantly improves generalization under diverse distribution shifts and multiple model architectures is proposed.
The Continuous Evolution Pool (CEP), a replay-free framework that maintains a dynamic pool of specialized forecasters, is proposed, which employs a retrieval mechanism to identify the nearest concept based on gene similarity, an evolution strategy to spawn new forecasters upon detecting distribution shifts, and an elim...
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