146 citations · 641 across the 84 of their papers we have counts for
87 papers
WONDER: A Radio World Model-based Negotiation Framework for Multi-Agent UAV Coverage Optimization
Jiahao Huang, Rongpeng Li, Zhifeng Zhao +2
Post-disaster damage to terrestrial infrastructure can disrupt wireless coverage,while Uncrewed Aerial Vehicle (UAV) swarms provide a promising solution for rapid restoration.Howev…
Agentic Router: An Execution-Grounded Continual Learning Approach With Memory
Yuxuan Chen, Rongpeng Li, Zhifeng Zhao +3
Large language model (LLM) agents provide a promising interface for command-line-based network operations, but a plausible command may still fail or introduce operational risk afte…
Adapting Diffusion Language Models for Lossless Pixel-Level Image Transmission
Tianqi Ren, Rongpeng Li, Xianfu Chen +2
Lossless pixel-level image transmission is a fundamental regime beyond semantic communications, because exact recovery requires both accurate symbol probability modeling and reliab…
Beyond Compromise: Pareto-Lenient Consensus for Efficient Multi-Preference LLM Alignment
Renxuan Tan, Rongpeng Li, Zhifeng Zhao +1
Transcending the single-preference paradigm, aligning LLMs with diverse human values is pivotal for robust deployment. Contemporary Multi-Objective Preference Alignment (MPA) appro…
Communications-Incentivized Collaborative Reasoning in NetGPT through Agentic Reinforcement Learning
Xiaoxue Yu, Rongpeng Li, Zhifeng Zhao +1
The evolution of next-Generation (xG) wireless networks marks a paradigm shift from connectivity-centric architectures to Artificial Intelligence (AI)-native designs that tightly i…
NetWorld: Communication-Based Diffusion World Model for Multi-Agent Reinforcement Learning in Wireless Networks
Kechen Meng, Rongpeng Li, Yansha Deng +2
As wireless communication networks grow in scale and complexity, diverse resource allocation tasks become increasingly critical. Multi-Agent Reinforcement Learning (MARL) provides…
In-Context Source and Channel Coding
Ziqiong Wang, Tianqi Ren, Rongpeng Li +2
Separate Source-Channel Coding (SSCC) remains attractive for text transmission due to its modularity and compatibility with mature entropy coders and powerful channel codes. Howeve…
Multi-Agent Conditional Diffusion Model with Mean Field Communication as Wireless Resource Allocation Planner
Kechen Meng, Sinuo Zhang, Rongpeng Li +5
In wireless communication systems, efficient and adaptive resource allocation plays a crucial role in enhancing overall Quality of Service (QoS). Compared to the conventional Model…
Optimizing NetGPT via Routing-Based Synergy and Reinforcement Learning
Yuxuan Chen, Rongpeng Li, Xianfu Chen +4
Large language model (LLM) agents at the network edge offer low-latency execution for routine queries. In contrast, complex requests often require the superior capability of cloud…
LLM-Empowered Agentic MAC Protocols: A Dynamic Stackelberg Game Approach
Renxuan Tan, Rongpeng Li, Fei Wang +4
Medium Access Control (MAC) protocols, essential for wireless networks, are typically manually configured. While deep reinforcement learning (DRL)-based protocols enhance task-spec…
RALLY: Role-Adaptive LLM-Driven Yoked Navigation for Agentic UAV Swarms
Ziyao Wang, Rongpeng Li, Sizhao Li +4
Intelligent control of Unmanned Aerial Vehicles (UAVs) swarms has emerged as a critical research focus, and it typically requires the swarm to navigate effectively while avoiding o…
Pareto Actor-Critic for Communication and Computation Co-Optimization in Non-Cooperative Federated Learning Services
Renxuan Tan, Rongpeng Li, Xiaoxue Yu +3
Federated learning (FL) in multi-service provider (SP) ecosystems is fundamentally hampered by non-cooperative dynamics, where privacy constraints and competing interests preclude…
AirLLM: Diffusion Policy-based Adaptive LoRA for Remote Fine-Tuning of LLM over the Air
Shiyi Yang, Xiaoxue Yu, Rongpeng Li +3
Operating Large Language Models (LLMs) on edge devices is increasingly challenged by limited communication bandwidth and strained computational and memory costs. Thus, cloud-assist…
Decentralized Consensus Inference-based Hierarchical Reinforcement Learning for Multi-Constrained UAV Pursuit-Evasion Game
Xiang Yuming, Li Sizhao, Li Rongpeng +2
Multiple quadrotor unmanned aerial vehicle (UAV) systems have garnered widespread research interest and fostered tremendous interesting applications, especially in multi-constraine…
Topology-Assisted Spatio-Temporal Pattern Disentangling for Scalable MARL in Large-scale Autonomous Traffic Control
Rongpeng Li, Jianhang Zhu, Jiahao Huang +2
Intelligent Transportation Systems (ITSs) have emerged as a promising solution towards ameliorating urban traffic congestion, with Traffic Signal Control (TSC) identified as a crit…
Tool-Aided Evolutionary LLM for Generative Policy Toward Efficient Resource Management in Wireless Federated Learning
Chongyang Tan, Ruoqi Wen, Rongpeng Li +3
Federated Learning (FL) enables distributed model training across edge devices in a privacy-friendly manner. However, its efficiency heavily depends on effective device selection a…
Reinforcement Learning-Based Heterogeneous Multi-Task Optimization in Semantic Broadcast Communications
Zhilin Lu, Rongpeng Li, Zhifeng Zhao +1
Semantic broadcast communications (Semantic BC) for image transmission have achieved significant performance gains for single-task scenarios. Nevertheless, extending these methods…
Multi-agent Uncertainty-Aware Pessimistic Model-Based Reinforcement Learning for Connected Autonomous Vehicles
Ruoqi Wen, Rongpeng Li, Xing Xu +1
Deep Reinforcement Learning (DRL) holds significant promise for achieving human-like Autonomous Vehicle (AV) capabilities, but suffers from low sample efficiency and challenges in…
Conditional Diffusion Model with OOD Mitigation as High-Dimensional Offline Resource Allocation Planner in Clustered Ad Hoc Networks
Kechen Meng, Sinuo Zhang, Rongpeng Li +3
Due to network delays and scalability limitations, clustered ad hoc networks widely adopt Reinforcement Learning (RL) for on-demand resource allocation. Albeit its demonstrated agi…
LLM4MAC: An LLM-Driven Reinforcement Learning Framework for MAC Protocol Emergence
Renxuan Tan, Rongpeng Li, Zhifeng Zhao
With the advent of 6G systems, emerging hyper-connected ecosystems necessitate agile and adaptive medium access control (MAC) protocols to contend with network dynamics and diverse…
Large-Scale AI in Telecom: Charting the Roadmap for Innovation, Scalability, and Enhanced Digital Experiences
Adnan Shahid, Adrian Kliks, Ahmed Al-Tahmeesschi +132
This white paper discusses the role of large-scale AI in the telecommunications industry, with a specific focus on the potential of generative AI to revolutionize network functions…
Robust Event-Triggered Integrated Communication and Control with Graph Information Bottleneck Optimization
Ziqiong Wang, Xiaoxue Yu, Rongpeng Li +1
Integrated communication and control serves as a critical ingredient in Multi-Agent Reinforcement Learning. However, partial observability limitations will impair collaboration eff…
Select2Drive: Pragmatic Communications for Real-Time Collaborative Autonomous Driving
Jiahao Huang, Jianhang Zhu, Rongpeng Li +2
Vehicle-to-everything communications-assisted autonomous driving has witnessed remarkable advancements in recent years, with pragmatic communications (PragComm) emerging as a promi…
Separate Source Channel Coding Is Still What You Need: An LLM-based Rethinking
Tianqi Ren, Rongpeng Li, Ming-min Zhao +5
Along with the proliferating research interest in Semantic Communication (SemCom), Joint Source Channel Coding (JSCC) has dominated the attention due to the widely assumed existenc…