AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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SpatialSpeak is introduced, a two-stage framework that connects QA-native reconstruction pretraining with spatial CoT learning and achieves state-of-the-art results on ReVSI, VSI-Bench, and SPAR-Bench, with a ReVSI score of 62.8 that exceeds the strongest compared baseline by 8.7 points.
This model matches optimization-based methods while delivering nearly 800x speedup, and surpasses the zero-shot performance of state-of-the-art generalizable models with markedly fewer parameters and reduced training/inference overhead, achieving an overall efficiency improvement.
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