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| Autores principales: | , , , , , , |
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| Formato: | Preprint |
| Publicado: |
2024
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| Materias: | |
| Acceso en línea: | https://arxiv.org/abs/2411.06193 |
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| _version_ | 1866929588574093312 |
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| author | Guo, Jie Wang, Meiting Yin, Hang Song, Bin Chi, Yuhao Yu, Fei Richard Yuen, Chau |
| author_facet | Guo, Jie Wang, Meiting Yin, Hang Song, Bin Chi, Yuhao Yu, Fei Richard Yuen, Chau |
| contents | Artificial intelligence generated content (AIGC) technologies, with a predominance of large language models (LLMs), have demonstrated remarkable performance improvements in various applications, which have attracted great interests from both academia and industry. Although some noteworthy advancements have been made in this area, a comprehensive exploration of the intricate relationship between AIGC and communication networks remains relatively limited. To address this issue, this paper conducts an exhaustive survey from dual standpoints: firstly, it scrutinizes the integration of LLMs and AIGC technologies within the domain of communication networks; secondly, it investigates how the communication networks can further bolster the capabilities of LLMs and AIGC. Additionally, this research explores the promising applications along with the challenges encountered during the incorporation of these AI technologies into communication networks. Through these detailed analyses, our work aims to deepen the understanding of how LLMs and AIGC can synergize with and enhance the development of advanced intelligent communication networks, contributing to a more profound comprehension of next-generation intelligent communication networks. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2411_06193 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Large Language Models and Artificial Intelligence Generated Content Technologies Meet Communication Networks Guo, Jie Wang, Meiting Yin, Hang Song, Bin Chi, Yuhao Yu, Fei Richard Yuen, Chau Information Theory Signal Processing Artificial intelligence generated content (AIGC) technologies, with a predominance of large language models (LLMs), have demonstrated remarkable performance improvements in various applications, which have attracted great interests from both academia and industry. Although some noteworthy advancements have been made in this area, a comprehensive exploration of the intricate relationship between AIGC and communication networks remains relatively limited. To address this issue, this paper conducts an exhaustive survey from dual standpoints: firstly, it scrutinizes the integration of LLMs and AIGC technologies within the domain of communication networks; secondly, it investigates how the communication networks can further bolster the capabilities of LLMs and AIGC. Additionally, this research explores the promising applications along with the challenges encountered during the incorporation of these AI technologies into communication networks. Through these detailed analyses, our work aims to deepen the understanding of how LLMs and AIGC can synergize with and enhance the development of advanced intelligent communication networks, contributing to a more profound comprehension of next-generation intelligent communication networks. |
| title | Large Language Models and Artificial Intelligence Generated Content Technologies Meet Communication Networks |
| topic | Information Theory Signal Processing |
| url | https://arxiv.org/abs/2411.06193 |