mlsanityData to 14 Oct 2026

A Comprehensive Survey of AI-Generated Content (AIGC): A History of Generative AI from GAN to ChatGPT

arXiv 2303.04226 ↗First posted 7 Mar 2023cs.AI cs.CL cs.LGcited by 224

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Cited by 24 in Diffusion models, but placed by its own abstract, which didn’t fit.

Abstract (arXiv)

Recently, ChatGPT, along with DALL-E-2 and Codex,has been gaining significant attention from society. As a result, many individuals have become interested in related resources and are seeking to uncover the background and secrets behind its impressive performance. In fact, ChatGPT and other Generative AI (GAI) techniques belong to the category of Artificial Intelligence Generated Content (AIGC), which involves the creation of digital content, such as images, music, and natural language, through AI models. The goal of AIGC is to make the content creation process more efficient and accessible, allowing for the production of high-quality content at a faster pace. AIGC is achieved by extracting and understanding intent information from instructions provided by human, and generating the content according to its knowledge and the intent information. In recent years, large-scale models have become increasingly important in AIGC as they provide better intent extraction and thus, improved generation results. With the growth of data and the size of the models, the distribution that the model can learn becomes more comprehensive and closer to reality, leading to more realistic and high-quality content generation. This survey provides a comprehensive review on the history of generative models, and basic components, recent advances in AIGC from unimodal interaction and multimodal interaction. From the perspective of unimodality, we introduce the generation tasks and relative models of text and image. From the perspective of multimodality, we introduce the cross-application between the modalities mentioned above. Finally, we discuss the existing open problems and future challenges in AIGC.

Key facts. Cited by 224 papers in the map (data through 14 Oct 2026). Builds on 222 of its 280 references that are in the map. First posted on arXiv 7 Mar 2023.

Builds on

222 of 280 references.

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Citing papers per year: 2023: 76; 2024: 82; 2025: 57; 2026: 9.

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  20. 2023Towards LLM-driven Dialogue State Trackingcited by 25
  21. 2023Stable Unlearnable Example: Enhancing the Robustness of Unlearnable Examples via Stable Error-Minimizing Noisecited by 25
  22. 2023Green Edge AI: A Contemporary Surveycited by 25
  23. 2024Bringing Generative AI to Adaptive Learning in Educationcited by 24
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  25. 2023AI-Generated Image Detection using a Cross-Attention Enhanced Dual-Stream Networkcited by 22
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  27. 2024CodePori: Large-Scale System for Autonomous Software Development Using Multi-Agent Technologycited by 22
  28. 2024Explainable Generative AI (GenXAI): A Survey, Conceptualization, and Research Agendacited by 22
  29. 2023Language as Reality: A Co-Creative Storytelling Game Experience in 1001 Nights using Generative AIcited by 21
  30. 2024I Think, Therefore I am: Benchmarking Awareness of Large Language Models Using AwareBenchcited by 21
  31. 2024ChatGPT as Research Scientist: Probing GPT's Capabilities as a Research Librarian, Research Ethicist, Data Generator and Data Predictorcited by 21
  32. 2025Representation Engineering for Large-Language Models: Survey and Research Challengescited by 21
  33. 2023Bias and Fairness in Chatbots: An Overviewcited by 20
  34. 2024Can Large Language Models Serve as Data Analysts? A Multi-Agent Assisted Approach for Qualitative Data Analysiscited by 20
  35. 2024Enhancing Zero-shot Text-to-Speech Synthesis with Human Feedbackcited by 20
  36. 2023Generative Agent-Based Modeling: Unveiling Social System Dynamics through Coupling Mechanistic Models with Generative Artificial Intelligencecited by 19
  37. 2024An overview of domain-specific foundation model: key technologies, applications and challengescited by 19
  38. 2024No Culture Left Behind: ArtELingo-28, a Benchmark of WikiArt with Captions in 28 Languagescited by 19

50 most cited of 224 All 224 (JSON)