# Generative Artificial Intelligence: A Systematic Review and Applications

arXiv: https://arxiv.org/abs/2405.11029 · HTML: https://mlsanity.com/paper/2405.11029/

## Key facts

- Cited by 37 papers in the map (data through 14 Oct 2026).
- Builds on 93 of its 168 references that are in the map.
- First posted on arXiv 17 May 2024.

## Builds on (most cited first, 30 of 93)

- [Attention Is All You Need](https://mlsanity.com/paper/1706.03762/) (2017)
- [BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding](https://mlsanity.com/paper/1810.04805/) (2018)
- [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)
- [GPT-4 Technical Report](https://mlsanity.com/paper/2303.08774/) (2023)
- [Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer](https://mlsanity.com/paper/1910.10683/) (2019)
- [Semi-Supervised Classification with Graph Convolutional Networks](https://mlsanity.com/paper/1609.02907/) (2016)
- [The Unreasonable Effectiveness of Deep Features as a Perceptual Metric](https://mlsanity.com/paper/1801.03924/) (2018)
- [BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehension](https://mlsanity.com/paper/1910.13461/) (2019)
- [Generative Adversarial Networks](https://mlsanity.com/paper/2203.00667/) (2022)
- [Image-to-Image Translation with Conditional Adversarial Networks](https://mlsanity.com/paper/1611.07004/) (2016)
- [Efficient Estimation of Word Representations in Vector Space](https://mlsanity.com/paper/1301.3781/) (2013)
- [Let's Verify Step by Step](https://mlsanity.com/paper/2305.20050/) (2023)
- [Deep Learning Face Attributes in the Wild](https://mlsanity.com/paper/1411.7766/) (2014)
- [Sequence to Sequence Learning with Neural Networks](https://mlsanity.com/paper/1409.3215/) (2014)
- [Improved Techniques for Training GANs](https://mlsanity.com/paper/1606.03498/) (2016)
- [Deep contextualized word representations](https://mlsanity.com/paper/1802.05365/) (2018)
- [Conditional Generative Adversarial Nets](https://mlsanity.com/paper/1411.1784/) (2014)
- [Density estimation using Real NVP](https://mlsanity.com/paper/1605.08803/) (2016)
- [A Survey on Bias and Fairness in Machine Learning](https://mlsanity.com/paper/1908.09635/) (2019)
- [SlowFast Networks for Video Recognition](https://mlsanity.com/paper/1812.03982/) (2018)
- [WebGPT: Browser-assisted question-answering with human feedback](https://mlsanity.com/paper/2112.09332/) (2021)
- [WaveNet: A Generative Model for Raw Audio](https://mlsanity.com/paper/1609.03499/) (2016)
- [Is Space-Time Attention All You Need for Video Understanding?](https://mlsanity.com/paper/2102.05095/) (2021)
- [ViViT: A Video Vision Transformer](https://mlsanity.com/paper/2103.15691/) (2021)
- [Explainable Artificial Intelligence (XAI): Concepts, Taxonomies, Opportunities and Challenges toward Responsible AI](https://mlsanity.com/paper/1910.10045/) (2019)
- [Glow: Generative Flow with Invertible 1x1 Convolutions](https://mlsanity.com/paper/1807.03039/) (2018)
- [Video Swin Transformer](https://mlsanity.com/paper/2106.13230/) (2021)
- [NICE: Non-linear Independent Components Estimation](https://mlsanity.com/paper/1410.8516/) (2014)
- [ChestX-ray8: Hospital-scale Chest X-ray Database and Benchmarks on Weakly-Supervised Classification and Localization of Common Thorax Diseases](https://mlsanity.com/paper/1705.02315/) (2017)

## Built on by (most cited first, 30 of 37)

- [Agentic AI: A Comprehensive Survey of Architectures, Applications, and Future Directions](https://mlsanity.com/paper/2510.25445/) (2025)
- [A review of faithfulness metrics for hallucination assessment in Large Language Models](https://mlsanity.com/paper/2501.00269/) (2024)
- [Boosting Relational Deep Learning with Pretrained Tabular Models](https://mlsanity.com/paper/2504.04934/) (2025)
- [GUI-Rise: Structured Reasoning and History Summarization for GUI Navigation](https://mlsanity.com/paper/2510.27210/) (2025)
- [EvalTalker: Learning to Evaluate Real-Portrait-Driven Multi-Subject Talking Humans](https://mlsanity.com/paper/2512.01340/) (2025)
- [Leveraging ASIC AI Chips for Homomorphic Encryption](https://mlsanity.com/paper/2501.07047/) (2025)
- [Aura-CAPTCHA: A Reinforcement Learning and GAN-Enhanced Multi-Modal CAPTCHA System](https://mlsanity.com/paper/2508.14976/) (2025)
- [REGEN: Real-Time Photorealism Enhancement in Games via a Dual-Stage Generative Network Framework](https://mlsanity.com/paper/2508.17061/) (2025)
- [Quantum Generative Adversarial Autoencoders: Learning latent representations for quantum data generation](https://mlsanity.com/paper/2509.16186/) (2025)
- [An evaluation of LLMs for generating movie reviews: GPT-4o, Gemini-2.0 and DeepSeek-V3](https://mlsanity.com/paper/2506.00312/) (2025)
- [The Role of Generative AI in Facilitating Social Interactions: A Scoping Review](https://mlsanity.com/paper/2506.10927/) (2025)
- [GenAI-based Multi-Agent Reinforcement Learning towards Distributed Agent Intelligence: A Generative-RL Agent Perspective](https://mlsanity.com/paper/2507.09495/) (2025)
- [Model selection in hybrid quantum neural networks with applications to quantum transformer architectures](https://mlsanity.com/paper/2603.21749/) (2026)
- [Quantum Generative Diffusion Model for Real-World Time Series](https://mlsanity.com/paper/2606.27561/) (2026)
- [Rethinking Automated Program Repair: The Impact of Bug Complexity, Fault Localization, and LLM Cost-efficiency](https://mlsanity.com/paper/2608.14065/) (2026)
- [GaNDLF-Synth: A Framework to Democratize Generative AI for (Bio)Medical Imaging](https://mlsanity.com/paper/2410.00173/) (2024)
- [Comparing Methods for Bias Mitigation in Graph Neural Networks](https://mlsanity.com/paper/2503.22569/) (2025)
- [Neuronal correlations shape the scaling behavior of memory capacity and nonlinear computational capability of reservoir recurrent neural networks](https://mlsanity.com/paper/2504.19657/) (2025)
- [Jarzynski Reweighting and Sampling Dynamics for Training Energy-Based Models: Theoretical Analysis of Different Transition Kernels](https://mlsanity.com/paper/2506.07843/) (2025)
- [Towards High Supervised Learning Utility Training Data Generation: Data Pruning and Column Reordering](https://mlsanity.com/paper/2507.10088/) (2025)
- [WaveLLDM: Design and Development of a Lightweight Latent Diffusion Model for Speech Enhancement and Restoration](https://mlsanity.com/paper/2508.21153/) (2025)
- [K-Syn: K-space Data Synthesis in Ultra Low-data Regimes](https://mlsanity.com/paper/2509.06997/) (2025)
- [Can generative AI figure out figurative language? The influence of idioms on essay scoring by ChatGPT, Gemini, and Deepseek](https://mlsanity.com/paper/2510.15009/) (2025)
- [GreenPlanner: Practical Floorplan Layout Generation via an Energy-Aware and Function-Feasible Generative Framework](https://mlsanity.com/paper/2512.00406/) (2025)
- [Toward Agentic Environments: GenAI and the Convergence of AI, Sustainability, and Human-Centric Spaces](https://mlsanity.com/paper/2512.15787/) (2025)
- [Topic Discovery and Classification for Responsible Generative AI Adaptation in Higher Education](https://mlsanity.com/paper/2512.16036/) (2025)
- [Stochastic Neural Networks for Quantum Devices](https://mlsanity.com/paper/2602.22241/) (2026)
- [Simulating Meaning, Nevermore! Introducing ICR: A Semiotic-Hermeneutic Metric for Evaluating Meaning in LLM Text Summaries](https://mlsanity.com/paper/2603.04413/) (2026)
- [HURRI-GAN: A Novel Approach for Hurricane Bias-Correction Beyond Gauge Stations using Generative Adversarial Networks](https://mlsanity.com/paper/2603.06649/) (2026)
- [Automated In-the-Wild Data Collection for Continual AI Generated Image Detection](https://mlsanity.com/paper/2605.02567/) (2026)

## Abstract (arXiv)

In recent years, the study of artificial intelligence (AI) has undergone a paradigm shift. This has been propelled by the groundbreaking capabilities of generative models both in supervised and unsupervised learning scenarios. Generative AI has shown state-of-the-art performance in solving perplexing real-world conundrums in fields such as image translation, medical diagnostics, textual imagery fusion, natural language processing, and beyond. This paper documents the systematic review and analysis of recent advancements and techniques in Generative AI with a detailed discussion of their applications including application-specific models. Indeed, the major impact that generative AI has made to date, has been in language generation with the development of large language models, in the field of image translation and several other interdisciplinary applications of generative AI. Moreover, the primary contribution of this paper lies in its coherent synthesis of the latest advancements in these areas, seamlessly weaving together contemporary breakthroughs in the field. Particularly, how it shares an exploration of the future trajectory for generative AI. In conclusion, the paper ends with a discussion of Responsible AI principles, and the necessary ethical considerations for the sustainability and growth of these generative models.