Control Systems and Computers

https://doi.org/10.15407/csc.2023.03.054

Control Systems and Computers, 2023, Issue 3 (303), pp. 54-60.

UDK 004.934

Dvoichenkov D.D., Ph.D. Student (Eng.), International Research and Training Center for Information Technologies and Systems of the NAS of Ukraine and MES of Ukraine, Glushkov ave, 40, Kyiv, 03187, Ukraine, ORCID: https://orcid.org/0009-0007-1935-6743, E-mail: supersokol777@gmail.com

Knowledge Graphs and Large Language Models

Large Language Models(LLM) based on the Transformer architecture is nowadays one of the most widely used tool in Natural Language Processing(NLP) field. Nonetheless this approach has some limitations and flaws. In particular, these problems become crucial for the NLP-based expert systems. The LLMs may sometimes hallucinate and provide non-trustworthy responses. We will advocate the using of Knowledge Graphs for solving this problem.

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Keywords: Knowledge Graphs, Large Language Models, Expert Systems, Natural Language Processing.

1. Vaswani, A., Shazeer, N., Parmar, N., Uszkoreit, J., Jones, L., Gomez, A.N., Kaiser, L. Polosukhin, I. (2017). Attention is all you need. Advances in neural information processing systems, 30. https://doi.org/10.48550/arXiv.1706.03762.
2. Chung, J.J.Y., Kamar, E., Amershi, S. (2023). Increasing Diversity While Maintaining Accuracy: Text Data Generation with Large Language Models and Human Interventions. In Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics , Vol. 1: Long Papers, pp. 575-593, Toronto, Canada. 
   https://doi.org/10.18653/v1/2023.acl-long.34
3. Zhang, W., Deng, Y., Liu, B., Pan, S. J., & Bing, L. (2023). Sentiment Analysis in the Era of Large Language Models: A Reality Check. https://doi.org/10.48550/arXiv.2305.15005.
4. Moslem, Y., Haque, R., Way, A. (2023). Adaptive machine translation with large language models. https://doi.org/10.48550/arXiv.2301.13294
5. Yao, B., Jiang, M., Yang, D., & Hu, J. (2023). Empowering LLM-based Machine Translation with Cultural Awareness. https://doi.org/10.48550/arXiv.2305.14328
6. Zhu, W., Liu, H., Dong, Q., Xu, J., Huang, S., Kong, L., Chen, J., Li, L. (2023). Multilingual machine translation with large language models: Empirical results and analysis. https://doi.org/10.48550/arXiv.2304.04675
7. Wu, Y., Jia, F., Zhang, S., Li, H., Zhu, E., Wang, Y., Lee Y.T., Peng R., Wu, Q., Wang, C. (2023). An Empirical Study on Challenging Math Problem Solving with GPT-4. https://doi.org/10.48550/arXiv.2306.01337
8. Poldrack, R. A., Lu, T., & Beguš, G. (2023). AI-assisted coding: Experiments with GPT-4. https://doi.org/10.48550/arXiv.2304.13187
9. Maus, N., Chao, P., Wong, E., & Gardner, J. R. (2023, August). Black box adversarial prompting for foundation models. In The Second Workshop on New Frontiers in Adversarial Machine Learning. [online]. Available at: <https://openreview.net/forum?id=aI5QPjTRbS > [Accessed: 23 Sept. 2023].
10. Zhao, W. X., Zhou, K., Li, J., Tang, T., Wang, X., Hou, Y., Min, Y., Zhang, B., Zhang, J., Dong, Z., Du, Y., Yang, Ch., Chen, Y., Chen, Zh., Jiang, J., Ren, R., Li, Y., Tang, X., Liu, Z., Liu, P., Nie, J.-Y., Wen, J.R. (2023). A survey of large language models. https://doi.org/10.48550/arXiv.2303.18223
11. Kaddour, J., Harris, J., Mozes, M., Bradley, H., Raileanu, R., McHardy, R. (2023). Challenges and applications of large language models. arXiv preprint arXiv:2307.10169. https://doi.org/10.48550/arXiv.2307.10169
12. Singhal, K., Tu, T., Gottweis, J., Sayres, R., Wulczyn, E., Hou, L., Clark, K., Pfohl, S., Cole-Lewis, H., Neal, D., Schaekermann, M., Wang, A., Amin, M., Lachgar, S., Mansfield, Ph., Prakash, S., Green, B., Dominowska, E., Arcas, B.A., Tomasev, N., Liu, Y., Semturs, Ch., Mahdavi, S.S., Barral, J., Webster, D., Corrado, G.S., Matias, Y., Azizi, Sh., Karthikesalingam, A., Natarajan, V. (2023). Towards expert-level medical question answering with large language models. https://doi.org/10.48550/arXiv.2305.09617
13. Choudhary, N., Reddy, C. K. (2023). Complex Logical Reasoning over Knowledge Graphs using Large Language Models. https://doi.org/10.48550/arXiv.2305.01157
14. Pan, S., Luo, L., Wang, Y., Chen, C., Wang, J., & Wu, X. (2023). Unifying Large Language Models and Knowledge Graphs: A Roadmap. https://doi.org/10.48550/arXiv.2306.08302
15. Hogan, A., Blomqvist, E., Cochez, M., d’Amato, C., Melo, G. D., Gutierrez, C., Gayo, J.E.L., Kirrane, S., Neumaier, S., Neumaier, A., Navigli, R., Schmelzeisen, L., Sequeda, J., Staab, S., Zimmermann, A. (2021). Knowledge graphs. ACM Computing Surveys (Csur), 54(4), pp. 1-37. https://doi.org/10.1145/3447772

 Received 21.10.2023