Federated Learning-Empowered AI-Generated Content in Wireless Networks
- URL: http://arxiv.org/abs/2307.07146v1
- Date: Fri, 14 Jul 2023 04:13:11 GMT
- Title: Federated Learning-Empowered AI-Generated Content in Wireless Networks
- Authors: Xumin Huang, Peichun Li, Hongyang Du, Jiawen Kang, Dusit Niyato, Dong
In Kim, Yuan Wu
- Abstract summary: Federated learning (FL) can be leveraged to improve learning efficiency and achieve privacy protection for AIGC.
We present FL-based techniques for empowering AIGC, and aim to enable users to generate diverse, personalized, and high-quality content.
- Score: 58.48381827268331
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: Artificial intelligence generated content (AIGC) has emerged as a promising
technology to improve the efficiency, quality, diversity and flexibility of the
content creation process by adopting a variety of generative AI models.
Deploying AIGC services in wireless networks has been expected to enhance the
user experience. However, the existing AIGC service provision suffers from
several limitations, e.g., the centralized training in the pre-training,
fine-tuning and inference processes, especially their implementations in
wireless networks with privacy preservation. Federated learning (FL), as a
collaborative learning framework where the model training is distributed to
cooperative data owners without the need for data sharing, can be leveraged to
simultaneously improve learning efficiency and achieve privacy protection for
AIGC. To this end, we present FL-based techniques for empowering AIGC, and aim
to enable users to generate diverse, personalized, and high-quality content.
Furthermore, we conduct a case study of FL-aided AIGC fine-tuning by using the
state-of-the-art AIGC model, i.e., stable diffusion model. Numerical results
show that our scheme achieves advantages in effectively reducing the
communication cost and training latency and privacy protection. Finally, we
highlight several major research directions and open issues for the convergence
of FL and AIGC.
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