A multi-layer cloud IDS uses per-layer ML detection, learned confidence gates, Chroma memory, and LLM escalation with Q-learning adaptive calibration to cut LLM calls by 58.78% while reporting 88.68% overall accuracy.
In-context learning in large language models (llms): Mechanisms, capabilities, and implications for advanced knowledge rep- resentation and reasoning
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A Multi-Layer Cloud-IDS Pipeline with LLM and Adaptive Q-Learning Calibration
A multi-layer cloud IDS uses per-layer ML detection, learned confidence gates, Chroma memory, and LLM escalation with Q-learning adaptive calibration to cut LLM calls by 58.78% while reporting 88.68% overall accuracy.