AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
Author
Chinese Information Processing Laboratory, Institute of Software, Chinese Academy of Sciences
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Joint Policy and Prompt Optimization (P O) is introduced to mitigate advantage collapse by alternating continuous policy updates with discrete prompt evolution, providing a self-reinforcing framework that facilitates more effective LLM alignment.
Inspired by the human cognitive planning process, HintNav-igator achieves state-of-the-art performance among open-source LLM agents, surpassing proprietary model Claude-3.5 Sonnet on the WebArena benchmark.
The first large-scale empirical study of SE skills in public repositories and marketplaces provides the first activity-centric characterization of SE skills and reveals how SE activities are increasingly being transformed into reusable skills.
DocOps is introduced, a deterministically verifiable evaluation framework underpinned by a hierarchical taxonomy that deconstructs document operations inspired by real-world practices into atomic dimensions and escalating workflow complexities that exposes the capability boundaries of agents in maintaining global docum...
Results support treating PHD as a distinct target for evaluating how LLMs formulate investigative directions when final conclusions are withheld, with gains for several lower-performing models on HypoArena but regressions for other systems, including a top-performing model.
A short-to-long OPD schedule that detects teacher-confirmed repetitive suffixes, treats the surviving prefix as each rollout's effective length, and allocates future rollout budgets to the effective lengths the policy can currently use is proposed.
Experimental results show that RUPA consistently outperforms existing UQ methods by providing more accurate uncertainty estimates, enabling earlier failure detection, and improving uncertainty-guided agent execution across diverse agent tasks.
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