AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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The Agent-Ass kernels outperform the Full-Agent artifacts across the evaluated definitions, indicating that expert-provided optimization directions, high-quality references, and workload context remain critical for reliable AI-driven kernel optimization.
This work proposes CVPO - Curriculum-guided Value-Variance Policy Optimization, a dynamic curriculum weighting method that adapts to question difficulty that achieves better performance and stronger exploration, enabling more accurate and robust reasoning in language models across various math tasks.
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