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Original Article

Pro Prompt-Dynamic persona-aware Prompt Construction for Robust LLM Reasoning Pipelines

  • Paper ID 1011
  • Volume 6, Issue 6
  • Pages 83-88
  • Published Online: November-December 2025
  • 5 Views
Open Access Peer Reviewed Crossref DOI

Authors

  • Dr C Lakshmi1
  • Pavan M R2
  • Tousif Ahmedd3
  • Punyashree C M4
  • Basavaraj S A5

1 2 3 4 5 Department of Computer Science Engineering Rajarajeswari College of Engineering Bangalore, Karnataka, India.

Article Information

Published Online
November-December 2025
Pages
83-88
Article Type
Original Article
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References

1. P. Sahoo, A. K. Singh, S. Saha, V. Jain, S. Mondal, and A. Chadha, “A Systematic Survey of Prompt Engineering in Large Language Models: Techniques and Applications,” arXiv preprint arXiv:2402.07927, Feb. 2024.: contentReference[oaicite:0] {index=0}
2. S. Vatsal and H. Dubey, “A Survey of Prompt Engineering Methods in Large Language Models for Different NLP Tasks,” arXiv preprint arXiv:2407.12994, Jul. 2024.: contentReference[oaicite:1] {index=1}
3. B. Chen, “Prompt Engineering for Large Language Models,” *Computers & Electrical Engineering*, 2025.: contentReference[oaicite:2] {index=2}
4. J. Jiang, F. Wang, J. Shen, S. Kim, and S. Kim, “A Survey on Large Language Models for Code Generation,” arXiv preprint arXiv:2406.00515, 2024.: contentReference[oaicite:3] {index=3}
5. F. Luo et al., “Leveraging Prompt Engineering in Large Language Models: Technique and Practice,” *ACS Publications*, 2025.: contentReference[oaicite:4] {index=4}
6. Y.-Y. Liu et al., “A Comprehensive Taxonomy of Prompt Engineering Techniques for Large Language Models,” *Frontiers of Computer Science*, vol. 20, article 2003601, 2026.: contentReference[oaicite:6] {index=6}
7. J. Shin, C. Tang, T. Mohati, M. Nayebi, S. Wang, and H. Hemmati, “Prompt Engineering or Fine Tuning: An Empirical Assessment of Large Language Models in Automated Software Engineering Tasks,” arXiv preprint arXiv: 2310.10508, Oct. 2023. contentReference[oaicite:7] {index=7}
8. J. Jiang, F. Wang, J. Shen, S. Kim & S. Kim, “A Survey on Large Language Models for Code Generation,” arXiv preprintarXiv: 2406.00515, 2024. contentReference[oaicite:0] {index=0}
9. B. Chen, “Unleashing the potential of prompt engineering for large language models,” Computers & Electrical Engineering, 2025.: content Reference[oaicite:1] {Index=1}
10. J. Gu, Z. Han, S. Chen, A. Beirami, B. He, G. Zhang, R. Liao, Y. Qin, V. Tresp & P. Torr, “A Systematic Survey of Prompt Engineering on Vision-Language Foundation Models,” arXiv preprint arXiv:2307.12980, 2023.: contentReference[oaicite:4] {index=4}
11. W. Yang, “A Comprehensive Survey on Integrating Large Language Models with Knowledge Bases,” Knowledge-Based Systems, 2025.: contentReference[oaicite:5] {index=5}
12. T. Debnath, “A Comprehensive Survey of Prompt Engineering Techniques in Large Language Models,” TechRxiv preprint, 2025.: contentReference[oaicite:6] {index=6}
13. W. C. Choi & C. I. Chang, “A Survey of Techniques, Design, Applications, Challenges, and Student Perspective of Chatbot-Based Learning Tutoring Systems Using LLMs,”
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