AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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It is found that user hostility varies 13-fold across models, driven largely by who each model attracts rather than by model behaviour: first-turn hostility spreads far wider than post-response hostility, and more than fifteenfold separates the extremes even after deduplicating opening prompts.
Strong standard-metric performance alone is insufficient to establish robustness after unlearning and motivate adversarial stress-testing as a complementary component of unlearning evaluation, showing a substantial gap between clean-query forgetting and adversarial robustness.
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