The rapid evolution of communication technologies has led to an explosion of standards, rendering traditional expert-dependent consultation methods inefficient and slow. To address this challenge, we propose \textbf{KG2QA}, a question answering (QA) framework for communication standards that integrates fine-tuned large language models (LLMs) with a domain-specific knowledge graph (KG) via a retrieval-augmented generation (RAG) pipeline. We construct a high-quality dataset of 6,587 QA pairs from ITU-T recommendations and fine-tune Qwen2.5-7B-Instruct, achieving significant performance gains: BLEU-4 increases from 18.86 to 66.90, outperforming both the base model and Llama-3-8B-Instruct. A structured KG containing 13,906 entities and 13,524 relations is built using LLM-assisted triple extraction based on a custom ontology. In our KG-RAG pipeline, the fine-tuned LLMs first retrieves relevant knowledge from KG, enabling more accurate and factually grounded responses. Evaluated by DeepSeek-V3 as a judge, the KG-enhanced system improves performance across five dimensions, with an average score increase of 2.26\%, demonstrating superior factual accuracy and relevance. Integrated with Web platform and API, KG2QA delivers an efficient and interactive user experience. Our code and data have been open-sourced https://github.com/luozhongze/KG2QA.

Few technological advancements bring to mind the American spirit of innovation like Henry Ford and his Model T. In the wake of his transportation innovation, the horse and buggy became an anachronism as the mass-produced automobile reshaped our cities, led to the emergence (for better or worse) of the suburbs, and revolutionized how we move goods and people. Ryan Hagemann (@RyanLeeHagemann) is the director of technology policy at the Niskanen Center, a libertarian issue advocacy organization based in Washington, DC. Now, there's little doubt that autonomous vehicles are the next frontier of transportation. These vehicles are projected to make our roads safer, potentially reducing fatalities by orders of magnitude. Along the way, however, there are a number of roadblocks to surmount: infrastructure issues, restrictive state licensing policies, driver education, cybersecurity and privacy vulnerabilities, and more.