no code implementations • 20 Apr 2024 • Feibo Jiang, Li Dong, Siwei Tu, Yubo Peng, Kezhi Wang, Kun Yang, Cunhua Pan, Dusit Niyato
Large Language Models (LLMs) have revolutionized natural language processing tasks.
no code implementations • 9 Mar 2024 • Feibo Jiang, Yubo Peng, Li Dong, Kezhi Wang, Kun Yang, Cunhua Pan, Xiaohu You
Semantic Communication (SC) is a novel paradigm for data transmission in 6G.
no code implementations • 13 Dec 2023 • Feibo Jiang, Li Dong, Yubo Peng, Kezhi Wang, Kun Yang, Cunhua Pan, Dusit Niyato, Octavia A. Dobre
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 requirements to LLMs by nature language.
no code implementations • 3 Sep 2023 • Feibo Jiang, Yubo Peng, Li Dong, Kezhi Wang, Kun Yang, Cunhua Pan, Xiaohu You
To this end, we propose a Large AI Model-based Multimodal SC (LAM-MSC) framework, in which we first present the MLM-based Multimodal Alignment (MMA) that utilizes the MLM to enable the transformation between multimodal and unimodal data while preserving semantic consistency.
no code implementations • 29 Aug 2023 • Li Dong, Feibo Jiang, Yubo Peng, Kezhi Wang, Kun Yang, Cunhua Pan, Robert Schober
Next-generation edge intelligence is anticipated to bring huge benefits to various applications, e. g., offloading systems.
no code implementations • 7 Jul 2023 • Feibo Jiang, Yubo Peng, Li Dong, Kezhi Wang, Kun Yang, Cunhua Pan, Xiaohu You
Semantic communication (SC) is an emerging intelligent paradigm, offering solutions for various future applications like metaverse, mixed-reality, and the Internet of everything.
no code implementations • 10 Apr 2023 • Huanjing Yue, Yubo Peng, Biting Yu, Xuanwu Yin, Zhenyu Zhou, Jingyu Yang
Based on this dataset, we further propose a Raw-HDRNet, which utilizes the raw LDR frames as inputs.