# Interactive AI with Retrieval-Augmented Generation for Next Generation Networking

arXiv: https://arxiv.org/abs/2401.11391 · HTML: https://mlsanity.com/paper/2401.11391/

## Key facts

- Cited by 34 papers in the map (data through 14 Oct 2026).
- Placed in Agentic RAG, agents and memory, one of 15 directions in Retrieval-augmented generation.
- Builds on 10 of its 19 references that are in the map.
- First posted on arXiv 21 Jan 2024.

## Placed in

- Retrieval-augmented generation / [Agentic RAG, agents and memory](https://mlsanity.com/rag/agentic-rag-agents-and-memory/)

## Builds on (most cited first, 10 of 10)

- [Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks](https://mlsanity.com/paper/2005.11401/) (2020)
- [The Rise and Potential of Large Language Model Based Agents: A Survey](https://mlsanity.com/paper/2309.07864/) (2023)
- [A Survey of Convolutional Neural Networks: Analysis, Applications, and Prospects](https://mlsanity.com/paper/2004.02806/) (2020)
- [Learning Graph Structures with Transformer for Multivariate Time Series Anomaly Detection in IoT](https://mlsanity.com/paper/2104.03466/) (2021)
- [Enhancing Deep Reinforcement Learning: A Tutorial on Generative Diffusion Models in Network Optimization](https://mlsanity.com/paper/2308.05384/) (2023)
- [Leveraging Explanations in Interactive Machine Learning: An Overview](https://mlsanity.com/paper/2207.14526/) (2022)
- [Transitioning to human interaction with AI systems: New challenges and opportunities for HCI professionals to enable human-centered AI](https://mlsanity.com/paper/2105.05424/) (2021)
- [Generative AI-enabled Vehicular Networks: Fundamentals, Framework, and Case Study](https://mlsanity.com/paper/2304.11098/) (2023)
- [Making Network Configuration Human Friendly](https://mlsanity.com/paper/2309.06342/) (2023)
- [An Interactive Query Generation Assistant using LLM-based Prompt Modification and User Feedback](https://mlsanity.com/paper/2311.11226/) (2023)

## Built on by (most cited first, 30 of 34)

- [Mobile Edge Intelligence for Large Language Models: A Contemporary Survey](https://mlsanity.com/paper/2407.18921/) (2024)
- [Generative AI Agents with Large Language Model for Satellite Networks via a Mixture of Experts Transmission](https://mlsanity.com/paper/2404.09134/) (2024)
- [A Systematic Review of Key Retrieval-Augmented Generation (RAG) Systems: Progress, Gaps, and Future Directions](https://mlsanity.com/paper/2507.18910/) (2025)
- [Toward Agentic AI: Generative Information Retrieval Inspired Intelligent Communications and Networking](https://mlsanity.com/paper/2502.16866/) (2025)
- [Blockchain for Large Language Model Security and Safety: A Holistic Survey](https://mlsanity.com/paper/2407.20181/) (2024)
- [Leveraging Fine-Tuned Retrieval-Augmented Generation with Long-Context Support: For 3GPP Standards](https://mlsanity.com/paper/2408.11775/) (2024)
- [Towards Efficient CoT Distillation: Self-Guided Rationale Selector for Better Performance with Fewer Rationales](https://mlsanity.com/paper/2509.23574/) (2025)
- [Hybrid RAG-empowered Multi-modal LLM for Secure Data Management in Internet of Medical Things: A Diffusion-based Contract Approach](https://mlsanity.com/paper/2407.00978/) (2024)
- [Unveiling and Mitigating Bias in Large Language Model Recommendations: A Path to Fairness](https://mlsanity.com/paper/2409.10825/) (2024)
- [Generative Semantic Communication for Joint Image Transmission and Segmentation](https://mlsanity.com/paper/2411.18005/) (2024)
- [SurgBox: Agent-Driven Operating Room Sandbox with Surgery Copilot](https://mlsanity.com/paper/2412.05187/) (2024)
- [Diffusion Models for Future Networks and Communications: A Comprehensive Survey](https://mlsanity.com/paper/2508.01586/) (2025)
- [Generative AI for Low-Carbon Artificial Intelligence of Things with Large Language Models](https://mlsanity.com/paper/2404.18077/) (2024)
- [When Graph Meets Retrieval Augmented Generation for Wireless Networks: A Tutorial and Case Study](https://mlsanity.com/paper/2412.07189/) (2024)
- [ORAN-GUIDE: RAG-Driven Prompt Learning for LLM-Augmented Reinforcement Learning in O-RAN Network Slicing](https://mlsanity.com/paper/2506.00576/) (2025)
- [Hippocampus: An Efficient and Scalable Memory Module for Agentic AI](https://mlsanity.com/paper/2602.13594/) (2026)
- [Large Language Model Empowered Next-Generation MIMO Networks: Fundamentals, Challenges, and Visions](https://mlsanity.com/paper/2404.08878/) (2024)
- [TeleOracle: Fine-Tuned Retrieval-Augmented Generation with Long-Context Support for Network](https://mlsanity.com/paper/2411.02617/) (2024)
- [Advancing Generative Artificial Intelligence and Large Language Models for Demand Side Management with Internet of Electric Vehicles](https://mlsanity.com/paper/2501.15544/) (2025)
- [LLM-Based Emulation of the Radio Resource Control Layer: Towards AI-Native RAN Protocols](https://mlsanity.com/paper/2505.16821/) (2025)
- [Agentic Satellite-Augmented Low-Altitude Economy and Terrestrial Networks: A Survey on Generative Approaches](https://mlsanity.com/paper/2507.14633/) (2025)
- [Reliable LLM-Based Edge-Cloud-Expert Cascades for Telecom Knowledge Systems](https://mlsanity.com/paper/2512.20012/) (2025)
- [Deep Learning Approaches for Anti-Money Laundering on Mobile Transactions: Review, Framework, and Directions](https://mlsanity.com/paper/2503.10058/) (2025)
- [BERT4beam: Large AI Model Enabled Generalized Beamforming Optimization](https://mlsanity.com/paper/2509.11056/) (2025)
- [An Agentic AI Framework with Large Language Models and Chain-of-Thought for UAV-Assisted Logistics Scheduling with Mobile Edge Computing](https://mlsanity.com/paper/2605.13221/) (2026)
- [Agentic Graph Retrieval-Augmented Generation for Auditable Commercial Registry Analysis](https://mlsanity.com/paper/2605.18770/) (2026)
- [The Roles of Generative Artificial Intelligence in Internet of Electric Vehicles](https://mlsanity.com/paper/2409.15750/) (2024)
- [Empowering Large Language Models in Wireless Communication: A Novel Dataset and Fine-Tuning Framework](https://mlsanity.com/paper/2501.09631/) (2025)
- [AGI Enabled Solutions For IoX Layers Bottlenecks In Cyber-Physical-Social-Thinking Space](https://mlsanity.com/paper/2506.22487/) (2025)
- [Asynchronous Risk-Aware Multi-Agent Packet Routing for Ultra-Dense LEO Satellite Networks](https://mlsanity.com/paper/2510.27506/) (2025)

## Abstract (arXiv)

With the advance of artificial intelligence (AI), the emergence of Google Gemini and OpenAI Q* marks the direction towards artificial general intelligence (AGI). To implement AGI, the concept of interactive AI (IAI) has been introduced, which can interactively understand and respond not only to human user input but also to dynamic system and network conditions. In this article, we explore an integration and enhancement of IAI in networking. We first comprehensively review recent developments and future perspectives of AI and then introduce the technology and components of IAI. We then explore the integration of IAI into the next-generation networks, focusing on how implicit and explicit interactions can enhance network functionality, improve user experience, and promote efficient network management. Subsequently, we propose an IAI-enabled network management and optimization framework, which consists of environment, perception, action, and brain units. We also design the pluggable large language model (LLM) module and retrieval augmented generation (RAG) module to build the knowledge base and contextual memory for decision-making in the brain unit. We demonstrate the effectiveness of the framework through case studies. Finally, we discuss potential research directions for IAI-based networks.