A systematic review of generative AI: importance of industry and startup-centered perspectives, agentic AI, ethical considerations & challenges, and future directions
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
Survey of Hallucination in Natural Language Generation
Ji, Z., Lee, N., Frieske, R., Yu, T., Su, D., Xu, Y., Ishii, E., Bang, Y. J., Madotto, A., & Fung, P. (2023) · ACM Computing Surveys · doi:10.1145/3571730 · Cited by 5,025 · see citing works
On the Opportunities and Risks of Foundation Models
Bommasani, R., Hudson, D. A., Adeli, E., Altman, R., Arora, S., von Arx, S., Bernstein, M. S., Bohg, J., Bosselut, A., Brunskill, E., et al. (2021) · arXiv · doi:10.48550/arxiv.2108.07258 · Cited by 2,676 · see citing works
Generative AI and ChatGPT: applications, challenges, and AI-human collaboration
Fui-Hoon Nah, F., Zheng, R., Cai, J., Siau, K., & Chen, L. (2023) · Journal of Information Technology Case and Application Research · doi:10.1080/15228053.2023.2233814 · Cited by 1,363 · see citing works
Deepfakes and beyond: A Survey of face manipulation and fake detection
Tolosana, R., Vera-Rodriguez, R., Fierrez, J., Morales, A., & Ortega-Garcia, J. (2020) · Information Fusion · doi:10.1016/j.inffus.2020.06.014 · Cited by 1,237 · see citing works
Lund, B. D., Wang, T., Mannuru, N. R., Nie, B., Shimray, S., & Wang, Z. (2023) · Journal of the Association for Information Science and Technology · doi:10.1002/asi.24750 · Cited by 919 · see citing works
Bahroun, Z., Anane, C., Ahmed, V., & Zacca, A. (2023) · Sustainability · doi:10.3390/su151712983 · Cited by 784 · see citing works
Agentic AI: Autonomous intelligence for complex goals–a comprehensive survey
Acharya, D. B., Kuppan, K., & Divya, B. (2025) · IEEE Access · doi:10.1109/access.2025.3532853 · Cited by 717 · see citing works
Bandi, A., Adapa, P. V. S. R., & Kuchi, Y. E. V. P. K. (2023) · Future Internet · doi:10.3390/fi15080260 · Cited by 638 · see citing works
Fabrication and errors in the bibliographic citations generated by ChatGPT
Walters, W. H., & Wilder, E. I. (2023) · Scientific Reports · doi:10.1038/s41598-023-41032-5 · Cited by 499 · see citing works
A survey on LLM-based multi-agent systems: Workflow, infrastructure, and challenges
Li, X., Wang, S., Zeng, S., Wu, Y., & Yang, Y. (2024) · Vicinagearth · doi:10.1007/s44336-024-00009-2 · Cited by 404 · see citing works
Using AI to write scholarly publications
Hosseini, M., Rasmussen, L. M., & Resnik, D. B. (2024) · Accountability in Research · doi:10.1080/08989621.2023.2168535 · Cited by 286 · see citing works
Batista, J., Mesquita, A., & Carnaz, G. (2024) · Information · doi:10.3390/info15110676 · Cited by 256 · see citing works
AI Agents vs. Agentic AI: A Conceptual Taxonomy, Applications and Challenges
Sapkota, R., Roumeliotis, K. I., & Karkee, M. (2025) · SuperIntelligence - Robotics - Safety & Alignment · doi:10.70777/si.v2i3.15161 · Cited by 186 · see citing works
Tool Learning with Foundation Models
Qin, Y., Hu, S., Lin, Y., Chen, W., Ding, N., Cui, G., Zeng, Z., Huang, Y., Xiao, C., Han, C., et al. (2023) · arXiv · doi:10.48550/arxiv.2304.08354 · Cited by 184 · see citing works
Poisoning Web-Scale Training Datasets is Practical
Carlini, N., Jagielski, M., Choquette-Choo, C. A., Paleka, D., Pearce, W., Anderson, H., Terzis, A., Thomas, K., & Tramèr, F. (2023) · arXiv · doi:10.48550/arxiv.2302.10149 · Cited by 138 · see citing works
Poisoning Web-Scale Training Datasets is Practical
Carlini, N., Jagielski, M., Choquette-Choo, C. A., Paleka, D., Pearce, W., Anderson, H., Terzis, A., Thomas, K., & Tramèr, F. (2024) · 2024 IEEE Symposium on Security and Privacy (SP) · doi:10.1109/sp54263.2024.00179 · Cited by 138 · see citing works
Deepfake Attacks: Generation, Detection, Datasets, Challenges, and Research Directions
Naitali, A., Ridouani, M., Salahdine, F., & Kaabouch, N. (2023) · Computers · doi:10.3390/computers12100216 · Cited by 117 · see citing works
Borger, J. G., Ng, A. P., Anderton, H., Ashdown, G. W., Auld, M., Blewitt, M. E., Brown, D. V., Call, M. J., Collins, P., Freytag, S., et al. (2023) · Immunology & Cell Biology · doi:10.1111/imcb.12689 · Cited by 103 · see citing works
AgentAI: A comprehensive survey on autonomous agents in distributed AI for industry 4.0
Piccialli, F., Chiaro, D., Sarwar, S., Cerciello, D., Qi, P., & Mele, V. (2025) · Expert Systems with Applications · doi:10.1016/j.eswa.2025.128404 · Cited by 77 · see citing works
Assess and Summarize: Improve Outage Understanding with Large Language Models
Jin, P., Zhang, S., Ma, M., Li, H., Kang, Y., Li, L., Liu, Y., Qiao, B., Zhang, C., Zhao, P., et al. (2023) · Proceedings of the 31st ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering · doi:10.1145/3611643.3613891 · Cited by 50 · see citing works
Agentic AI Frameworks in SMMEs: A Systematic Literature Review of Ecosystemic Interconnected Agents
Olujimi, P. A., Owolawi, P. A., Mogase, R. C., & Wyk, E. V. (2025) · doi:10.20944/preprints202504.1797.v1 · Cited by 36 · see citing works
Coding agents: A comprehensive survey of automated bug fixing systems and benchmarks
Puvvadi, M., Arava, S. K., Santoria, A., Chennupati, S. S. P., & Puvvadi, H. V. (2025) · 2025 IEEE 14th International Conference on Communication Systems and Network Technologies (CSNT) · doi:10.1109/csnt64827.2025.10968728 · Cited by 4 · see citing works
Flagged first, then by citations
- Authors
- Patel, K., Shah, M., Qureshi, K. M., & Qureshi, M. R. N.
- Venue
- Artificial Intelligence Review
- Published
- 2025-11-12
- Volume
- 59
- Issue
- 1
- ISSN
- 1573-7462
- Cited by
- 32
- References
- 22
- Language
- en
- Licence
- Funders
- Deanship of Scientific Research at King Khalid University, Saudi Arabia (RGP.2/624/46)
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review