Have a personal or library account? Click to login
Achieving Efficient Prompt Engineering in Large Language Models Using a Hybrid and Multi-Objective Optimization Framework Cover

Achieving Efficient Prompt Engineering in Large Language Models Using a Hybrid and Multi-Objective Optimization Framework

Open Access
|Jun 2025

References

  1. Pornprasit, Chanathip, C. Tantithamthavorn. Fine-Tuning and Prompt Engineering for Large Language Models-Based Code Review Automation. – Information and Software Technology, Vol. 175, 2024, 107523.
  2. Heston, T. F., C. Khun. Prompt Engineering in Medical Education. – International Medical Education, Vol. 2, 2023, No 3, pp. 198-205.
  3. He, X., S. Zannettou, Y. Shen, Y. Zhang. You only Prompt Once: On the Capabilities of Prompt Learning on Large Language Models to Tackle Toxic Content. – In: 2024 IEEE Symposium on Security and Privacy (SP’24), 2024, pp. 770-787.
  4. Sabbatella, A., A. Ponti, I. Giordani, A. Candelieri, F. Archetti. Prompt Optimization in Large Language Models. – Mathematics, Vol. 12, 2024, No 6, p. 929.
  5. Song, Y. F., Y. Q. He, X. F. Zhao, H. L. Gu, D. Jiang, H. J. Yang, L. X. Fan. A Communication Theory Perspective on Prompting Engineering Methods for Large Language Models. – Journal of Computer Science and Technology, Vol. 39, 2024, No 4, pp. 984-1004.
  6. Knoth, N., A. Tolzin, A. Janson, J. M. Leimeister. AI Literacy and Its Implications for Prompt Engineering Strategies. – Computers and Education: Artificial Intelligence, Vol. 6, 2024, 100225.
  7. Liu, S., X. Chen, Qu, K. Tang, Y. S. Ong. Large Language Models as Evolutionary Optimizers. – In: 2024 IEEE Congress on Evolutionary Computation (CEC’24), June 2024, pp. 1-8.
  8. He, C., Y. Tian, Z. Lu. Artificial Evolutionary Intelligence (AEI): Evolutionary Computation Evolves with Large Language Models. – Journal of Membrane Computing, 2024, pp. 1-18.
  9. Patania, S., E. Masiero, L. Brini, V. Piskovskyi, D. Ognibene, G. Donabauer, U. Kruschwitz. Large Language Models as an Active Bayesian Filter: Information Acquisition and Integration. – In: Proc. of 28th Workshop on the Semantics and Pragmatics of Dialogue, September 2024.
  10. Chen, S., W. Wang, X. Chen, M. Zhang, P. Lu, X. Li, Y. Du. Enhancing Chinese Comprehension and Reasoning for Large Language Models: An Efficient LoRA Fine-Tuning and Tree of Thoughts Framework. – Journal of Supercomputing, Vol. 81, 2025, No 1, p. 50.
  11. Klyuchnikov, N., I. Trofimov, E. Artemova, M. Salnikov, M. Fedorov, A. Filippov, E. Burnaev. Nas-Bench-Nlp: Neural Architecture Search Benchmark for Natural Language Processing. – IEEE Access, Vol. 10, 2022, pp. 45736-45747.
  12. Zhao, B., W. Jin, Y. Zhang, S. Huang, G. Yang. Prompt Learning for Metonymy Resolution: Enhancing Performance with Internal Prior Knowledge of Pre-Trained Language Models. – Knowledge-Based Systems, Vol. 279, 2023, 110928.
  13. De Curtò, J., I. de Zarzà, G. Roig, J. C. Cano, P. Manzoni, C. T. Calafate. Llm-Informed Multi-Armed Bandit Strategies for Non-Stationary Environments. – Electronics, Vol. 12, 2023, No 13, 2814.
  14. Ahmed, A., X. Zeng, R. Xi, M. Hou, S. A. Shah. MED-Prompt: A Novel Prompt Engineering Framework for Medicine Prediction on Free-Text Clinical Notes. – Journal of King Saud University-Computer and Information Sciences, Vol. 36, 2024, No 2, 101933.
  15. Liu, S., C. Chen, X. Qu, K. Tang, Y. S. Ong. Large Language Models as Evolutionary Optimizers. – In: Proc. of IEEE Congress on Evolutionary Computation (CEC’24), June 2024, pp. 1-8.
  16. Sorokin, L., D. Safin, Sh. Nejati. Can Search-Based Testing with Pareto Optimization Effectively Cover Failure-Revealing Test Inputs? – Empirical Software Engineering, Vol. 30, 2025, No 1, pp. 1-39.
  17. Kumar, S., D. Deepika, K. Slater, V. Kumar. AOPWIKI-EXPLORER: An Interactive Graph-Based Query Engine Leveraging Large Language Models. – Computational Toxicology, Vol. 30, 2024, 100308.
  18. Qiu, Y., Y. Jin. ChatGPT and Finetuned BERT: A Comparative Study for Developing Intelligent Design Support Systems. – Intelligent Systems with Applications, Vol. 21, 2024, 200308.
  19. GLUE Dataset. https://www.kaggle.com/datasets/thedevastator/nli-dataset-for-sentence-understanding
  20. Soni, U., D. A. G. Gordhan Jethava, A. Ganatra. Latest Advancements in Credit Risk Assessment with Machine Learning and Deep Learning Techniques. – Cybernetics and Information Technologies, Vol. 24, 2024, No 4, pp. 22-44.
  21. Ngo, V. B., V. H. Vu. Multi-Level Machine Learning Model to Improve the Effectiveness of Predicting Customer Churn in Banks. – Cybernetics and Information Technologies, Vol. 24, 2024, No 3, pp. 3-20.
  22. Vincent, A. M., P. Jidesh. An Improved Hyperparameter Optimization Framework for AutoML Systems Using Evolutionary Algorithms. – Scientific Reports, Vol. 13, 2023, No 1, 4737.
  23. Bakır, H., Ö. Ceviz. Empirical Enhancement of Intrusion Detection Systems: A Comprehensive Approach with Genetic Algorithm-Based Hyperparameter Tuning and Hybrid Feature Selection. – Arabian Journal for Science and Engineering, Vol. 49, 2024, No 9, pp. 13025-13043.
  24. Al Saba, M. T., N. A. Hakami, K. S. AlJebreen, M. A. Abido. Multi-Objective Distributionally Robust Approach for Optimal Location of Renewable Energy Sources. – Alexandria Engineering Journal, Vol. 77, 2023, pp. 75-94.
  25. Harane, P. P., D. R. Unune, R. Ahmed, S. Wojciechowski. Multi-Objective Optimization for Electric Discharge Drilling of Waspaloy: A Comparative Analysis of NSGA-II, MOGA, MOGWO, and MOPSO. – Alexandria Engineering Journal, Vol. 99, 2024, pp. 1-16.
  26. GSM8K Dataset Link. https://www.kaggle.com/datasets/thedevastator/grade-school-math-8k-q-a
DOI: https://doi.org/10.2478/cait-2025-0012 | Journal eISSN: 1314-4081 | Journal ISSN: 1311-9702
Language: English
Page range: 67 - 82
Submitted on: Mar 11, 2025
Accepted on: May 4, 2025
Published on: Jun 25, 2025
Published by: Bulgarian Academy of Sciences, Institute of Information and Communication Technologies
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year

© 2025 Sridevi Kottapalli Narayanaswamy, Rajanna Muniswamy, published by Bulgarian Academy of Sciences, Institute of Information and Communication Technologies
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.