activity
20232025
most citedLarge AI Model Empowered Multimodal Semantic Communications

5 citations · 18 across the 16 of their papers we have counts for

collaborators

16 papers

cs.NI2025

Smart-TCP: An Agentic AI-based Autonomous and Adaptive TCP Protocol

Yule Han, Kezhi Wang, Yizhe Zhao +1

The Transmission Control Protocol (TCP) relies on deterministic state machines and sequence-number arithmetic to ensure reliable communication. However, hard-coded protocol logic i…

cs.AI2025

SemAgent: Semantic-Driven Agentic AI Empowered Trajectory Prediction in Vehicular Networks

Lin Zhu, Kezhi Wang, Luping Xiang +1

Efficient information exchange and reliable contextual reasoning are essential for vehicle-to-everything (V2X) networks. Conventional communication schemes often incur significant…

cs.NI2025

A Unified Cloud-Edge-Terminal Framework for Multimodal Integrated Sensing and Communication

Yubo Peng, Luping Xiang, Kun Yang +3

The transition to 6G calls for tightly integrated sensing and communication to support mission-critical services such as autonomous driving, embodied AI, and high-precision telemed…

cs.LG2025

SIMAC: A Semantic-Driven Integrated Multimodal Sensing And Communication Framework

Yubo Peng, Luping Xiang, Kun Yang +3

Traditional single-modality sensing faces limitations in accuracy and capability, and its decoupled implementation with communication systems increases latency in bandwidth-constra…

cs.IT2025

CommGPT: A Graph and Retrieval-Augmented Multimodal Communication Foundation Model

Feibo Jiang, Wanyun Zhu, Li Dong +4

Large Language Models (LLMs) possess human-level cognitive and decision-making capabilities, making them a key technology for 6G. However, applying LLMs to the communication domain…

cs.IT2025★ 1 cited

FlashSAM: Lightweight Vision Model for Multi-UAV Token Communication in Low-Latitude Wireless Networks

Feibo Jiang, Siwei Tu, Li Dong +5

Token Communication (TokenCom) is a promising paradigm for low-altitude wireless networks, as it focuses on transmitting task-relevant core information, particularly in environment…

cs.IT2025★ 1 cited

M4SC: An MLLM-based Multi-modal, Multi-task and Multi-user Semantic Communication System

Feibo Jiang, Siwei Tu, Li Dong +3

Multi-modal Large Language Models (MLLMs) are capable of precisely extracting high-level semantic information from multi-modal data, enabling multi-task understanding and generatio…

cs.LG2024

GAI-Enabled Explainable Personalized Federated Semi-Supervised Learning

Yubo Peng, Feibo Jiang, Li Dong +2

Federated learning (FL) is a commonly distributed algorithm for mobile users (MUs) training artificial intelligence (AI) models, however, several challenges arise when applying FL…

cs.LG2024

Personalized Federated Learning for Generative AI-Assisted Semantic Communications

Yubo Peng, Feibo Jiang, Li Dong +2

Semantic Communication (SC) focuses on transmitting only the semantic information rather than the raw data. This approach offers an efficient solution to the issue of spectrum reso…

cs.CV2024

Visual Language Model based Cross-modal Semantic Communication Systems

Feibo Jiang, Chuanguo Tang, Li Dong +3

Semantic Communication (SC) has emerged as a novel communication paradigm in recent years, successfully transcending the Shannon physical capacity limits through innovative semanti…

cs.LG2024★ 1 cited

Personalized Wireless Federated Learning for Large Language Models

Feibo Jiang, Li Dong, Siwei Tu +5

Large language models (LLMs) have driven profound transformations in wireless networks. However, within wireless environments, the training of LLMs faces significant challenges rel…

cs.IT2024★ 3 cited

Large Generative Model Assisted 3D Semantic Communication

Feibo Jiang, Yubo Peng, Li Dong +4

Semantic Communication (SC) is a novel paradigm for data transmission in 6G. However, there are several challenges posed when performing SC in 3D scenarios: 1) 3D semantic extracti…

cs.AI2023★ 1 cited

Large Language Model Enhanced Multi-Agent Systems for 6G Communications

Feibo Jiang, Li Dong, Yubo Peng +5

The rapid development of the Large Language Model (LLM) presents huge opportunities for 6G communications, e.g., network optimization and management by allowing users to input task…

cs.AI2023★ 5 cited

Large AI Model Empowered Multimodal Semantic Communications

Feibo Jiang, Li Dong, Yubo Peng +4

Multimodal signals, including text, audio, image, and video, can be integrated into Semantic Communication (SC) systems to provide an immersive experience with low latency and high…

cs.AI2023★ 2 cited

LAMBO: Large AI Model Empowered Edge Intelligence

Li Dong, Feibo Jiang, Yubo Peng +4

Next-generation edge intelligence is anticipated to benefit various applications via offloading techniques. However, traditional offloading architectures face several issues, inclu…

cs.AI2023★ 4 cited

Large AI Model-Based Semantic Communications

Feibo Jiang, Yubo Peng, Li Dong +4

Semantic communication (SC) is an emerging intelligent paradigm, offering solutions for various future applications like metaverse, mixed reality, and the Internet of Everything. H…