# Artificial General Intelligence (AGI)-Native Wireless Systems: A Journey Beyond 6G

arXiv: https://arxiv.org/abs/2405.02336 · HTML: https://mlsanity.com/paper/2405.02336/

## Key facts

- Cited by 31 papers in the map (data through 14 Oct 2026).
- Builds on 54 of its 110 references that are in the map.
- First posted on arXiv 29 Apr 2024.

## Builds on (most cited first, 30 of 54)

- [A Simple Framework for Contrastive Learning of Visual Representations](https://mlsanity.com/paper/2002.05709/) (2020)
- [Sparks of Artificial General Intelligence: Early experiments with GPT-4](https://mlsanity.com/paper/2303.12712/) (2023)
- [Self-Supervised Learning from Images with a Joint-Embedding Predictive Architecture](https://mlsanity.com/paper/2301.08243/) (2023)
- [Understanding the Effects of RLHF on LLM Generalisation and Diversity](https://mlsanity.com/paper/2310.06452/) (2023)
- [PlanBench: An Extensible Benchmark for Evaluating Large Language Models on Planning and Reasoning about Change](https://mlsanity.com/paper/2206.10498/) (2022)
- [Understanding Dimensional Collapse in Contrastive Self-supervised Learning](https://mlsanity.com/paper/2110.09348/) (2021)
- [Neurosymbolic AI: The 3rd Wave](https://mlsanity.com/paper/2012.05876/) (2020)
- [Contrastive Learning of Structured World Models](https://mlsanity.com/paper/1911.12247/) (2019)
- [A Vision of 6G Wireless Systems: Applications, Trends, Technologies, and Open Research Problems](https://mlsanity.com/paper/1902.10265/) (2019)
- [Consciousness in Artificial Intelligence: Insights from the Science of Consciousness](https://mlsanity.com/paper/2308.08708/) (2023)
- [When Foundation Model Meets Federated Learning: Motivations, Challenges, and Future Directions](https://mlsanity.com/paper/2306.15546/) (2023)
- [Igniting Language Intelligence: The Hitchhiker's Guide From Chain-of-Thought Reasoning to Language Agents](https://mlsanity.com/paper/2311.11797/) (2023)
- [Grounding Physical Concepts of Objects and Events Through Dynamic Visual Reasoning](https://mlsanity.com/paper/2103.16564/) (2021)
- [Less Data, More Knowledge: Building Next Generation Semantic Communication Networks](https://mlsanity.com/paper/2211.14343/) (2022)
- [Large Language Models Empowered Autonomous Edge AI for Connected Intelligence](https://mlsanity.com/paper/2307.02779/) (2023)
- [Toward a 6G AI-Native Air Interface](https://mlsanity.com/paper/2012.08285/) (2020)
- [Temporal Abstraction in Reinforcement Learning with the Successor Representation](https://mlsanity.com/paper/2110.05740/) (2021)
- [A Theoretical Perspective on Hyperdimensional Computing](https://mlsanity.com/paper/2010.07426/) (2020)
- [When Large Language Model Agents Meet 6G Networks: Perception, Grounding, and Alignment](https://mlsanity.com/paper/2401.07764/) (2024)
- [The Essential Role of Causality in Foundation World Models for Embodied AI](https://mlsanity.com/paper/2402.06665/) (2024)
- [Large Multi-Modal Models (LMMs) as Universal Foundation Models for AI-Native Wireless Systems](https://mlsanity.com/paper/2402.01748/) (2024)
- [Wireless Multi-Agent Generative AI: From Connected Intelligence to Collective Intelligence](https://mlsanity.com/paper/2307.02757/) (2023)
- [Compositional generalization through abstract representations in human and artificial neural networks](https://mlsanity.com/paper/2209.07431/) (2022)
- [Explainable Reinforcement Learning via a Causal World Model](https://mlsanity.com/paper/2305.02749/) (2023)
- [Experienced Deep Reinforcement Learning with Generative Adversarial Networks (GANs) for Model-Free Ultra Reliable Low Latency Communication](https://mlsanity.com/paper/1911.03264/) (2019)
- [Neuro-Symbolic Causal Reasoning Meets Signaling Game for Emergent Semantic Communications](https://mlsanity.com/paper/2210.12040/) (2022)
- [A Survey of Beam Management for mmWave and THz Communications Towards 6G](https://mlsanity.com/paper/2308.02135/) (2023)
- [Holographic MIMO Surfaces for 6G Wireless Networks: Opportunities, Challenges, and Trends](https://mlsanity.com/paper/1911.12296/) (2019)
- [AI-native Interconnect Framework for Integration of Large Language Model Technologies in 6G Systems](https://mlsanity.com/paper/2311.05842/) (2023)
- [Towards Causal Foundation Model: on Duality between Causal Inference and Attention](https://mlsanity.com/paper/2310.00809/) (2023)

## Built on by (most cited first, 30 of 31)

- [TSpec-LLM: An Open-source Dataset for LLM Understanding of 3GPP Specifications](https://mlsanity.com/paper/2406.01768/) (2024)
- [Towards Agentic AI Networking in 6G: A Generative Foundation Model-as-Agent Approach](https://mlsanity.com/paper/2503.15764/) (2025)
- [R-SFLLM: Jamming Resilient Framework for Split Federated Learning with Large Language Models](https://mlsanity.com/paper/2407.11654/) (2024)
- [World Model-Based Learning for Long-Term Age of Information Minimization in Vehicular Networks](https://mlsanity.com/paper/2505.01712/) (2025)
- [IQFM A Wireless Foundational Model for I/Q Streams in AI-Native 6G](https://mlsanity.com/paper/2506.06718/) (2025)
- [Dual-Mind World Models: A General Framework for Learning in Dynamic Wireless Networks](https://mlsanity.com/paper/2510.24546/) (2025)
- [Structured Latent Dynamics in Wireless CSI via Homomorphic World Models](https://mlsanity.com/paper/2603.20048/) (2026)
- [Edge General Intelligence Through World Models and Agentic AI: Fundamentals, Solutions, and Challenges](https://mlsanity.com/paper/2508.09561/) (2025)
- [Multi-Modal Data-Enhanced Foundation Models for Prediction and Control in Wireless Networks: A Survey](https://mlsanity.com/paper/2601.03181/) (2026)
- [Enhancing Spectrum Efficiency in 6G Satellite Networks: A GAIL-Powered Policy Learning via Asynchronous Federated Inverse Reinforcement Learning](https://mlsanity.com/paper/2409.18718/) (2024)
- [Intelligent Orchestration of Distributed Large Foundation Model Inference at the Edge](https://mlsanity.com/paper/2504.03668/) (2025)
- [Towards a Foundation Model for Communication Systems](https://mlsanity.com/paper/2505.14603/) (2025)
- [Joint Partitioning and Placement of Foundation Models for Real-Time Edge AI](https://mlsanity.com/paper/2512.01039/) (2025)
- [Large Model Enabled Embodied Intelligence for 6G Integrated Perception, Communication, and Computation Network](https://mlsanity.com/paper/2512.15109/) (2025)
- [World Model-Enabled Causal Digital Twins for Semantic Communications in Physical AI Systems](https://mlsanity.com/paper/2605.16547/) (2026)
- [Hypergame Theory for Decentralized Resource Allocation in Multi-user Semantic Communications](https://mlsanity.com/paper/2409.17985/) (2024)
- [Distilling Large Language Models for Network Active Queue Management](https://mlsanity.com/paper/2501.16734/) (2025)
- [Agentic AI-Based Joint Computing and Networking via Mixture of Experts and Large Language Models](https://mlsanity.com/paper/2605.02911/) (2026)
- [6G Communication Networks Enabling Embodied Agents: Architecture and Prototype](https://mlsanity.com/paper/2605.23263/) (2026)
- [SCoTT: Strategic Chain-of-Thought Tasking for Wireless-Aware Robot Navigation in Digital Twins](https://mlsanity.com/paper/2411.18212/) (2024)
- [R-MTLLMF: Resilient Multi-Task Large Language Model Fusion at the Wireless Edge](https://mlsanity.com/paper/2411.18220/) (2024)
- [SafeCOMM: A Study on Safety Degradation in Fine-Tuned Telecom Large Language Models](https://mlsanity.com/paper/2506.00062/) (2025)
- [Distributionally Robust Wireless Semantic Communication with Large AI Models](https://mlsanity.com/paper/2506.03167/) (2025)
- [AGI Enabled Solutions For IoX Layers Bottlenecks In Cyber-Physical-Social-Thinking Space](https://mlsanity.com/paper/2506.22487/) (2025)
- [Large-Scale Model Enabled Semantic Communication Based on Robust Knowledge Distillation](https://mlsanity.com/paper/2508.02148/) (2025)
- [Vehicle-to-Infrastructure Collaborative Spatial Perception via Multimodal Large Language Models](https://mlsanity.com/paper/2509.03837/) (2025)
- [BRAIN: Bayesian Reasoning via Active Inference for Agentic and Embodied Intelligence in Mobile Networks](https://mlsanity.com/paper/2602.14033/) (2026)
- [Strategic Bidding in 6G Spectrum Auctions with Large Language Models](https://mlsanity.com/paper/2604.24156/) (2026)
- [From Passive Mirrors to Active Agents: Holonic Digital Twins for Physical AI over Networks](https://mlsanity.com/paper/2608.06227/) (2026)
- [X-RACE: XAI-assisted Recurrent neural network Attribution for Channel Estimation](https://mlsanity.com/paper/2609.11211/) (2026)

## Abstract (arXiv)

Building future wireless systems that support services like digital twins (DTs) is challenging to achieve through advances to conventional technologies like meta-surfaces. While artificial intelligence (AI)-native networks promise to overcome some limitations of wireless technologies, developments still rely on AI tools like neural networks. Such tools struggle to cope with the non-trivial challenges of the network environment and the growing demands of emerging use cases. In this paper, we revisit the concept of AI-native wireless systems, equipping them with the common sense necessary to transform them into artificial general intelligence (AGI)-native systems. These systems acquire common sense by exploiting different cognitive abilities such as perception, analogy, and reasoning, that enable them to generalize and deal with unforeseen scenarios. Towards developing the components of such a system, we start by showing how the perception module can be built through abstracting real-world elements into generalizable representations. These representations are then used to create a world model, founded on principles of causality and hyper-dimensional (HD) computing, that aligns with intuitive physics and enables analogical reasoning, that define common sense. Then, we explain how methods such as integrated information theory play a role in the proposed intent-driven and objective-driven planning methods that maneuver the AGI-native network to take actions. Next, we discuss how an AGI-native network can enable use cases related to human and autonomous agents: a) analogical reasoning for next-generation DTs, b) synchronized and resilient experiences for cognitive avatars, and c) brain-level metaverse experiences like holographic teleportation. Finally, we conclude with a set of recommendations to build AGI-native systems. Ultimately, we envision this paper as a roadmap for the beyond 6G era.