AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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The results support a circuit-level interpretation of LLM safety and suggest that mechanistic abstractions can reveal stable and transferable patterns underlying aligned behavior.
Experiments on diverse open-source text classification datasets show that AHR can outperform standard baselines like LoRA when learning from limited samples, despite having 200-1000x fewer trainable parameters, as the authors' AHR only modifies ~0.0001% of the model's parameters.
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