AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
5 papers indexed here
We haven’t gathered this author’s papers yet. Follow them and we’ll fetch their work.
Not the right person? Other researchers publish under this name.
Results characterize when runtime-controlled composition of coding-agent products improves execution accuracy, as well as when runtime-controlled composition of coding-agent products improves execution accuracy.
GEARS (Generative Engine for Agentic Ranking Systems), a framework that reframes ranking optimization as an autonomous discovery process within a programmable experimentation environment, and incorporates validation hooks to enforce statistical robustness and filter out brittle policies that overfit short-term signals.
Amid the rapid advancement of physical-world intelligence, cloud-edge collaborative large language models (LLMs) have emerged as a promising roadmap for practical LLM deployment. However, existing cloud-edge paradigms struggle to balance global consensus with local personalization, which fails to satisfy the need for a...
Together, these studies show how explicit natural-language intent can be carried into feed recommendation under a precision-first evaluation framework.
This work synthesizes a task-conditioned temporal workflow graph that jointly specifies agent connectivity and edge-level communication semantics, and introduces ReActNet, a training-free framework that compiles a query and a set of role-specialized agents into a sequence of directed communication graphs.
We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.