AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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AgentSWE is introduced, a benchmark for agent software engineering spanning three stages of the agent development lifecycle: Creation of a complete agent from a natural-language requirement, Editing of production agent codebases, and Optimization toward a measurable target.
This work introduces AREX, a family of Recursively Self-Improving (RSI) deep research agents that substantially outperforms comparable-scale baselines and remains competitive with models using substantially more activated parameters.
EvoResearcher is presented, a training-free, inference-time protocol that adds cost-bounded self-reflection to a single frozen LLM backbone and establishes cross-domain behavior on GSM8K and MATH on the same frozen backbone.
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