AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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The results indicate that Micro-Collaborative Poisoning is not driven by a single dominant poisoned passage, but by the accumulation of weak adversarial signals across retrieved sources, which achieves downstream influence while leaving a weaker explicit poisoning signature than direct poisoning.
This study evaluates the generalization capability of models such as LGBM, RF, XGB, and LSTM, particularly in identifying previously unseen attacks, and investigated the impact of feature selection on generalization and examined how performance changes when combining different datasets.
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