3 citations · 6 across the 10 of their papers we have counts for
10 papers
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…
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…
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…
Adaptive Layer Splitting for Wireless LLM Inference in Edge Computing: A Model-Based Reinforcement Learning Approach
Yuxuan Chen, Rongpeng Li, Xiaoxue Yu +2
Optimizing the deployment of large language models (LLMs) in edge computing environments is critical for enhancing privacy and computational efficiency. Toward efficient wireless L…
Snake Learning: A Communication- and Computation-Efficient Distributed Learning Framework for 6G
Xiaoxue Yu, Xingfu Yi, Rongpeng Li +4
In the evolution towards 6G, integrating Artificial Intelligence (AI) with advanced network infrastructure emerges as a pivotal strategy for enhancing network intelligence and reso…
Communication-Efficient Soft Actor-Critic Policy Collaboration via Regulated Segment Mixture
Xiaoxue Yu, Rongpeng Li, Chengchao Liang +1
Multi-Agent Reinforcement Learning (MARL) has emerged as a foundational approach for addressing diverse, intelligent control tasks in various scenarios like the Internet of Vehicle…
Alternate Learning based Sparse Semantic Communications for Visual Transmission
Siyu Tong, Xiaoxue Yu, Rongpeng Li +3
Semantic communication (SemCom) demonstrates strong superiority over conventional bit-level accurate transmission, by only attempting to recover the essential semantic information…
Communication-Efficient Cooperative Multi-Agent PPO via Regulated Segment Mixture in Internet of Vehicles
Xiaoxue Yu, Rongpeng Li, Fei Wang +4
Multi-Agent Reinforcement Learning (MARL) has become a classic paradigm to solve diverse, intelligent control tasks like autonomous driving in Internet of Vehicles (IoV). However,…