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Concordia University
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Despite high diagnostic accuracy, LLMs fail to choose valid recovery actions for over 60% of incidents, exposing a critical flaw in their operational utility.
Forget retraining: this SDN-IoT defense system uses LLMs to safely evolve reinforcement learning policies through interpretable policy updates, slashing catastrophic overloads by 80%.
