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.
This research addresses organizational data transformation by integrating Information Science (IS) and Natural Language Processing (NLP).We argue that Large Language Model (LLM) failures in data interaction tasks (instantiated via text-to-sql), such as hallucinations, stem from applications detached from information go...
This paper explores automated data transformation using intelligent rule-based systems to address the limitations of traditional ETL processes, which are often manual, rigid, and error-prone. The proposed approach integrates rule-based reasoning with metadata-driven transformation to handle complex data from heterogene...
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.
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