AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
TL;DR
An intelligent Q&A system based on a traceable knowledge graph and prompt enhancement technology that guides large language models to accurately output corresponding page URLs in response to user queries is proposed.
SAFAARI (Schema-Aware Framework for Accelerated Advertiser Response Intelligence), a multi-agent framework that addresses the critical bottleneck of schema linking in Natural Language to SQL (NL-to-SQL) systems through specialized content, metadata, and orchestration agents, is presented.
Validation through nine use cases demonstrates the architecture is functionally effective, generating accurate database queries matching ground-truth and identifying invalid relationships without exposing raw transactional data to the LLM.
The study concludes that intelligent rule-based systems offer a scalable and efficient solution for modern data transformation in big data and real-time environments.
A literature-based architectural framework for reliable knowledge retrieval systems that separates external knowledge management from LLM-based reasoning and generation is developed and indicates that reliable LLM deployment should be treated as an end-to-end architectural problem rather than solely a model-performance...
This work presents SCOUT (Selective Context Optimization for Universal Tooling for Universal Tooling), which reframes tool exposure as a context-selection problem, injecting only tools relevant to the current step, and reduces MCP tool-token consumption by 99%, cutting per-query inference cost at enterprise scale.
This demo presents cuRPQ +, a GPU-based engine and interactive system for extended CRPQs with three representative path constraints: word equality, prefix, and bounded length, which supports these constraints within a unified execution framework.
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