Presentation Details
Prompting Strategies for Large Language Models: A Structured Review of Techniques, Applications, and Open Challenges
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Updated Time：2026-07-22 16:09:19 Hits：15
Online
Start Time：2026-07-30 18:05（Asia/Kolkata）
Duration：15min
Session：S6 Artificial Intelligence Use Cases »
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Abstract
Prompting strategies for large language models, including chain-of-thought reasoning, few-shot demonstrations, instruction tuning, and automatic prompt optimisation, have become central to how practitioners extract useful behaviour from these systems without modifying model weights. Recent growth in research on these methods has produced a wide and fragmented body of work that spans reasoning benchmarks, medical applications, code generation, and multilingual settings. This paper presents a comprehensive review of sixty-three studies published between 2021 and 2025, covering commonly examined technique categories, datasets, evaluation approaches, and reported limitations. Stepwise reasoning formats, in-context learning, zero-shot instruction following, soft prompt tuning, and agent-style iterative prompting have each shown meaningful improvements over baseline approaches across diverse task types. A systematic review process is used to compare performance trends and surface recurring limitations such as output sensitivity to phrasing, the absence of standardised benchmarks, prompt injection vulnerabilities, and limited multilingual coverage. The study draws attention to future directions including security-aware prompting, cross-lingual adaptation, explainable prompt analysis, and unified evaluation infrastructure. Taken together, the reviewed work demonstrates that prompt engineering has matured into a field with genuine technical depth, though several foundational problems remain unresolved.
Keywords
Prompt Engineering, Large Language Models, Chain-of-Thought Prompting, Few-Shot Learning, Instruction Tuning, Automatic Prompt Optimization, Agentic Prompting, Natural Language Processing
Speaker
Heera Patwal
Education Graphic Era Hill UniversitySubmission Author
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Important Date
-
Conference Date
Jul 30
2026
toAug 01
2026
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Jul 28 2026
Registration deadline
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Jul 30 2026
Draft paper submission deadline
Sponsored By
The United Societies of Science
Organized By
Kongunadu College of Engineering and Technology
Supported By
IEEE Section
IEEE Madras Section
IEEE Madras Section
Contact Information
Previous Conferences
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2026-07-30 India Trichy
2026 International Conference on Networks Computers and Communications
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