AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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STR-Agent is proposed, an LLM-driven framework for QoS-aware routing in LEO satellite networks that significantly outperforms conventional baselines, and results demonstrate the potential of LLM-driven agent architectures to enable serviceaware and adaptive QoS routing in future LEO satellite networks.
Experiments show that HiRS-Agent substantially improves long-horizon tool-use capability and final-task correctness, demonstrating the effectiveness of structured multi-agent collaboration for reliable RS agents.
GeoChrono is proposed, an MLLM with enhanced capabilities for tracing, memorizing, and reasoning about long-term geographic evolution, surpassing the leading commercial MLLMs by over 20%, while C2FComp reduces visual tokens by over 56% while retaining GeoChrono's 94.6% performance on ChronoBench.
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