AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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EviGraph is presented, a deep-search framework that separates search execution from evidence recording while using a shared policy for the trainable roles, enabling reinforcement learning to directly supervise evidence construction rather than only the final answer.
This work introduces SocialBuddy, the first agentic search framework tailored for social scenarios, and constructs SocialEnv, the first large-scale simulated environment for social search, which delivers multi-scale guidance in complex long-sequence scenarios.
Influence-Aware Policy Optimization (IAPO), which represents each rollout as a typed influence-dependency graph over trainable agent actions, with user and tool observations serving as evidence, is introduced and advances the understanding of credit assignment in multi-turn user interactions.
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