AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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XRepoSkill, a trajectory-based approach for learning transferable skills that achieves the highest issue resolution rate in all six benchmark--LLM combinations, and is evaluated on the challenging long-horizon DeepSWE benchmark.
SWE-MILE is proposed, an asynchronous potential-induced milestone credit assignment framework that derives fine-grained process supervision from workflow runtime, without auxiliary reward models or external evaluators, and demonstrates substantial improvements in agent performance.
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.
This survey aims to clarify the conceptual boundaries of self-evolving coding agents and provide a foundation for designing more adaptive, reliable, and software-aware agentic systems.
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