# LLM-Twin: Mini-Giant Model-driven Beyond 5G Digital Twin Networking Framework with Semantic Secure Communication and Computation

arXiv: https://arxiv.org/abs/2312.10631 · HTML: https://mlsanity.com/paper/2312.10631/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- Builds on 14 of its 44 references that are in the map.
- First posted on arXiv 17 Dec 2023.

## Builds on (most cited first, 14 of 14)

- [QLoRA: Efficient Finetuning of Quantized LLMs](https://mlsanity.com/paper/2305.14314/) (2023)
- [The Reversal Curse: LLMs trained on "A is B" fail to learn "B is A"](https://mlsanity.com/paper/2309.12288/) (2023)
- [AudioPaLM: A Large Language Model That Can Speak and Listen](https://mlsanity.com/paper/2306.12925/) (2023)
- [Digital Twin of Wireless Systems: Overview, Taxonomy, Challenges, and Opportunities](https://mlsanity.com/paper/2202.02559/) (2022)
- [Low-latency Federated Learning and Blockchain for Edge Association in Digital Twin empowered 6G Networks](https://mlsanity.com/paper/2011.09902/) (2020)
- [6G Digital Twin Networks: From Theory to Practice](https://mlsanity.com/paper/2212.02032/) (2022)
- [Mini-DALLE3: Interactive Text to Image by Prompting Large Language Models](https://mlsanity.com/paper/2310.07653/) (2023)
- [A Survey on Digital Twins: Architecture, Enabling Technologies, Security and Privacy, and Future Prospects](https://mlsanity.com/paper/2301.13350/) (2023)
- [Causal Semantic Communication for Digital Twins: A Generalizable Imitation Learning Approach](https://mlsanity.com/paper/2304.12502/) (2023)
- [Generative AI-driven Semantic Communication Framework for NextG Wireless Network](https://mlsanity.com/paper/2310.09021/) (2023)
- [The Paradigm of Digital Twin Communications](https://mlsanity.com/paper/2105.07182/) (2021)
- [Digital Twin-Empowered Smart Attack Detection System for 6G Edge of Things Networks](https://mlsanity.com/paper/2310.03554/) (2023)
- [Mini-Giants: "Small" Language Models and Open Source Win-Win](https://mlsanity.com/paper/2307.08189/) (2023)
- [Digital Twin-Enabled Intelligent DDoS Detection Mechanism for Autonomous Core Networks](https://mlsanity.com/paper/2310.12924/) (2023)

## Built on by (most cited first, 4 of 4)

- [Large Language Models for UAVs: Current State and Pathways to the Future](https://mlsanity.com/paper/2405.01745/) (2024)
- [A Survey on Large Language Models for Communication, Network, and Service Management: Application Insights, Challenges, and Future Directions](https://mlsanity.com/paper/2412.19823/) (2024)
- [Future-Proofing Mobile Networks: A Digital Twin Approach to Multi-Signal Management](https://mlsanity.com/paper/2407.15520/) (2024)
- [AgenticTwin: An Agentic LLM Framework Integrated with Digital Twin for Anomaly Detection](https://mlsanity.com/paper/2608.11679/) (2026)

## Abstract (arXiv)

Beyond 5G networks provide solutions for next-generation communications, especially digital twins networks (DTNs) have gained increasing popularity for bridging physical space and digital space. However, current DTNs networking frameworks pose a number of challenges especially when applied in scenarios that require high communication efficiency and multimodal data processing. First, current DTNs frameworks are unavoidable regarding high resource consumption and communication congestion because of original bit-level communication and high-frequency computation, especially distributed learning-based DTNs. Second, current machine learning models for DTNs are domain-specific (e.g. E-health), making it difficult to handle DT scenarios with multimodal data processing requirements. Last but not least, current security schemes for DTNs, such as blockchain, introduce additional overheads that impair the efficiency of DTNs. To address the above challenges, we propose a large language model (LLM) empowered DTNs networking framework, LLM-Twin. First, we design the mini-giant model collaboration scheme to achieve efficient deployment of LLM in DTNs, since LLM are naturally conducive to processing multimodal data. Then, we design a semantic-level high-efficiency, and secure communication model for DTNs. The feasibility of LLM-Twin is demonstrated by numerical experiments and case studies. To our knowledge, this is the first to propose LLM-based semantic-level digital twin networking framework.