AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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This work introduces RecreationWorld, a five-platform framework built around recreation: given a running reference, an agent must discover its behavior and build a faithful implementation with no prescribed workflow, and introduces RecreationBench, comprising 250 diverse tasks across domains and platforms.
Terminal-Universe is introduced, a framework which turns each trajectory into a reusable environment and explores it for synthesizing new tasks and continued interactions, and produces 37.3k task-sufficient environments.
It is demonstrated that the hidden states of probed answers more effectively differentiate distinct solution paths than semantic embeddings, and the perplexity of probed answers serves as a practical proxy for reasoning correctness.
Qwen-CUA is introduced, a native computer-use agent with a 397B-A17B Qwen mixture-of-experts backbone that outperforms Qwen3.7 and remains competitive with leading proprietary systems, and scalable verifiable interaction and hybrid tool use as key directions.
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