AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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SPRII, a training principle that uses relations between interactions as weak supervision for persistent context while retaining the learner's native objective, is introduced.
Orthogonal Decomposition for Social Recommendation (ODSR) is proposed, an embedding-space framework that orthogonally decomposes the aggregated social message into an aligned component and an orthogonal deviation, and learns a dimension-wise vector gate to regulate the deviation under ranking supervision.
OODA-Tool, a typed closed-loop policy designed to mitigate state preservation from action realization, consistently improves task success across model sizes, with larger gains on smaller models and on tasks whose actions depend strongly on information accumulated across turns and prior tool results.
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