# AIGC In China: Current Developments And Future Outlook

arXiv: https://arxiv.org/abs/2308.08451 · HTML: https://mlsanity.com/paper/2308.08451/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- Builds on 14 of its 45 references that are in the map.
- First posted on arXiv 14 Aug 2023.

## Builds on (most cited first, 14 of 14)

- [Attention Is All You Need](https://mlsanity.com/paper/1706.03762/) (2017)
- [Learning Transferable Visual Models From Natural Language Supervision](https://mlsanity.com/paper/2103.00020/) (2021)
- [Language Models are Few-Shot Learners](https://mlsanity.com/paper/2005.14165/) (2020)
- [High-Resolution Image Synthesis with Latent Diffusion Models](https://mlsanity.com/paper/2112.10752/) (2021)
- [Training language models to follow instructions with human feedback](https://mlsanity.com/paper/2203.02155/) (2022)
- [Proximal Policy Optimization Algorithms](https://mlsanity.com/paper/1707.06347/) (2017)
- [Finetuned Language Models Are Zero-Shot Learners](https://mlsanity.com/paper/2109.01652/) (2021)
- [Multimodal Machine Learning: A Survey and Taxonomy](https://mlsanity.com/paper/1705.09406/) (2017)
- [Aligning Text-to-Image Models using Human Feedback](https://mlsanity.com/paper/2302.12192/) (2023)
- [A Comprehensive Survey of AI-Generated Content (AIGC): A History of Generative AI from GAN to ChatGPT](https://mlsanity.com/paper/2303.04226/) (2023)
- [A Complete Survey on Generative AI (AIGC): Is ChatGPT from GPT-4 to GPT-5 All You Need?](https://mlsanity.com/paper/2303.11717/) (2023)
- [AI-Generated Content (AIGC): A Survey](https://mlsanity.com/paper/2304.06632/) (2023)
- [High-dimensional Clustering onto Hamiltonian Cycle](https://mlsanity.com/paper/2304.14531/) (2023)
- [The current opportunities and challenges of Web 3.0](https://mlsanity.com/paper/2306.03351/) (2023)

## Built on by (most cited first, 2 of 2)

- [A Comprehensive Survey in LLM(-Agent) Full Stack Safety: Data, Training and Deployment](https://mlsanity.com/paper/2504.15585/) (2025)
- [Innovative Digital Storytelling with AIGC: Exploration and Discussion of Recent Advances](https://mlsanity.com/paper/2309.14329/) (2023)

## Abstract (arXiv)

The increasing attention given to AI Generated Content (AIGC) has brought a profound impact on various aspects of daily life, industrial manufacturing, and the academic sector. Recognizing the global trends and competitiveness in AIGC development, this study aims to analyze China's current status in the field. The investigation begins with an overview of the foundational technologies and current applications of AIGC. Subsequently, the study delves into the market status, policy landscape, and development trajectory of AIGC in China, utilizing keyword searches to identify relevant scholarly papers. Furthermore, the paper provides a comprehensive examination of AIGC products and their corresponding ecosystem, emphasizing the ecological construction of AIGC. Finally, this paper discusses the challenges and risks faced by the AIGC industry while presenting a forward-looking perspective on the industry's future based on competitive insights in AIGC.