AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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Static benchmarks for large language model (LLM) agents face saturation and data contamination risks, motivating continual updates to evaluation tasks. However, aggregate scores and success rates offer limited insight into specific problem-solving bottlenecks and provide limited guidance for subsequent task design. We...
This work formalizes Salience Induction as truth-preserving edits that redirect Multi-Hop attribute binding while leaving the retrieval trace semantically intact, and defines six Salience-Editing operator classes and builds an iterative proposer-verifier pipeline under factual and stealth constraints.
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