AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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M$^2$PFN is proposed, an end-to-end framework that turns this tabular foundation model into a multimodal AD predictor, and transfers even when the cognitive instrument changes.
Together, these results identify when TabPFN can serve as a training-free head for calibration-sensitive multimodal classification and show that representation adaptation and reliable head choice are complementary.
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