AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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This paper designs a Dual-Branch Spatio-Temporal Graph Convolutional Network with Transformer with a robust loss function to suppress the effect of extreme outliers and proposes a feature-separation prediction method for bus arrival time.
Experiments on traditional Mongolian text summarization tasks demonstrate that the proposed Nucleus-to-Periphery Retrieval-Iterative Prompting method significantly out-performs multiple baseline models on automatic evaluation metrics including ROUGE-1, ROUGE-2, and ROUGE-L.
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