# Automatic Retrieval-augmented Generation of 6G Network Specifications for Use Cases

arXiv: https://arxiv.org/abs/2405.03122 · HTML: https://mlsanity.com/paper/2405.03122/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 6 May 2024.

## Built on by (most cited first, 2 of 2)

- [KP-A: A Unified Network Knowledge Plane for Catalyzing Agentic Network Intelligence](https://mlsanity.com/paper/2507.08164/) (2025)
- [Agentic Assistant for 6G: Turn-based Conversations for AI-RAN Hierarchical Co-Management](https://mlsanity.com/paper/2602.13868/) (2026)

## Abstract (arXiv)

6G Open Radio Access Networks (O-RAN) promises to open data interfaces to enable plug-and-play service Apps, many of which are consumer and business-facing. Opening up 6G access lowers the barrier to innovation but raises the challenge that the required communication specifications are not fully known to all service designers. As such, business innovators must either be familiar with 6G standards or consult with experts. Enabling consistent, unbiased, rapid, and low-cost requirement assessment and specification generation is crucial to the O-RAN innovation ecosystem. Here, we discuss our initiative to bridge service specification gaps between network service providers and business innovators leveraging Large Language Models (LLMs). We first review the state-of-the-art and motivation in 6G plug-and-play services, capabilities, potential use cases and LLMs. We identify an ample innovation space for hybrid use cases that may require diverse and variational wireless functionalities across its operating time. We show that the network specification can be automated and present the first automatic retrieval-augmented network service specification framework for 6G use cases. To enable public acceptance and feedback, a website interface is published for the research and industrial community to experiment with the framework. We hope this review highlights the need for emerging foundation models for this area and motivates researcher engagement and contribution to the community through our framework.