AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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Adapting general-purpose large language models to specific tasks requires substantial human effort in designing data and training strategies. Sustaining improvement is especially challenging because model updates change the error distribution, requiring strategies to be continually refined. We introduce ImproveAnyTask,...
GS-IQA is proposed, a framework that reformulates IQA as a progressive Where--What--How diagnosis, emulating the human perceptual process from an initial glance to closer scrutiny, and consistently surpasses state-of-the-art methods in distortion localization, recognition, and severity estimation.
A systematic empirical analysis demonstrates that standard metrics including COMET, XCOMET, and BERTScore exhibit near-zero or negative correlation with human cultural judgments, and even display a severity inversion in which scores increase as translation quality deteriorates, and proposes CuRIL, a reinforcement learn...
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