# Towards Resilient and Autonomous Networks: A BlueSky Vision on AI-Native 6G

arXiv: https://arxiv.org/abs/2605.21395 · HTML: https://mlsanity.com/paper/2605.21395/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 16 of its 44 references that are in the map.
- First posted on arXiv 20 May 2026.

## Builds on (most cited first, 16 of 16)

- [Chronos: Learning the Language of Time Series](https://mlsanity.com/paper/2403.07815/) (2024)
- [Chronos-2: From Univariate to Universal Forecasting](https://mlsanity.com/paper/2510.15821/) (2025)
- [Mobile Edge Intelligence for Large Language Models: A Contemporary Survey](https://mlsanity.com/paper/2407.18921/) (2024)
- [Toto: Time Series Optimized Transformer for Observability](https://mlsanity.com/paper/2407.07874/) (2024)
- [Large Language Models for Telecom: Forthcoming Impact on the Industry](https://mlsanity.com/paper/2308.06013/) (2023)
- [6G Wireless Systems: Vision, Requirements, Challenges, Insights, and Opportunities](https://mlsanity.com/paper/2008.03213/) (2020)
- [Foundation Models for Time Series: A Survey](https://mlsanity.com/paper/2504.04011/) (2025)
- [Large-Scale AI in Telecom: Charting the Roadmap for Innovation, Scalability, and Enhanced Digital Experiences](https://mlsanity.com/paper/2503.04184/) (2025)
- [LLM for Mobile: An Initial Roadmap](https://mlsanity.com/paper/2407.06573/) (2024)
- [A Survey on Low Latency Towards 5G: RAN, Core Network and Caching Solutions](https://mlsanity.com/paper/1708.02562/) (2017)
- [6G Cellular Networks and Connected Autonomous Vehicles](https://mlsanity.com/paper/2010.00972/) (2020)
- [TelecomTS: A Multi-Modal Observability Dataset for Time Series and Language Analysis](https://mlsanity.com/paper/2510.06063/) (2025)
- [Integrated 6G TN and NTN Localization: Challenges, Opportunities, and Advancements](https://mlsanity.com/paper/2501.13488/) (2025)
- [5G Enabled Fault Detection and Diagnostics: How Do We Achieve Efficiency?](https://mlsanity.com/paper/2202.07521/) (2022)
- [Toward Wireless Human-Machine Collaboration in the 6G Era](https://mlsanity.com/paper/2602.22662/) (2026)
- [Reforming the Mechanism: Editing Reasoning Patterns in LLMs with Circuit Reshaping](https://mlsanity.com/paper/2603.06923/) (2026)

## Built on by (most cited first, 1 of 1)

- [AnyJev Technical Report](https://mlsanity.com/paper/2610.00831/) (2026)

## Abstract (arXiv)

The proliferation of emerging applications, such as autonomous driving and immersive experiences, demands cellular networks that are not only faster, but fundamentally more resilient and autonomous. This paper presents a BlueSky vision on how Artificial Intelligence will be natively integrated into 6G, shifting the paradigm from underlineNetwork for AI to underlineAI for Network. We envision that, unlike 5G's reliance on scattered, ad-hoc models each trained for a single task, native AI in the 6G era will be anchored by a foundation model and and orchestrated via collaborative multi-agent systems, framing network management as a unified, multi-modal, multi-task optimization problem. Built on this vision, we outline two transformative directions. The first focuses on developing a 6G foundation model as a unified backbone, with task-specific knowledge distilled into compact models suited for diverse edge deployments. The second advances multi-agent systems designed to autonomously diagnose, maintain, and recover networks with minimal human intervention. These directions chart a roadmap for 6G to evolve into an intelligent, self-sustaining communication infrastructure.