Related Research

📚 Research on Prompt Techniques

Prompt engineering is an evolving field, and several research papers explore techniques that enhance interactions with language models. Below are some key papers that discuss various prompting strategies and their applications.

We aim to incorporate insights from these research papers and resources like Prompt Engineering Guide into promptrefiner, aligning its prompt-enhancement strategies with state-of-the-art methodologies in prompt engineering.

🔍 Key Research Papers

1. A Systematic Survey of Prompt Engineering in Large Language Models: Techniques and Applications
   Pranab Sahoo et al. (2024)
   This paper provides a structured overview of prompt engineering methods, categorizing them by application and discussing their strengths and limitations.

2. The Prompt Report: A Systematic Survey of Prompting Techniques
   Sander Schulhoff et al. (2024)
   A comprehensive survey assembling a taxonomy of prompting techniques, analyzing their applications and providing a vocabulary of related terms.

3. Prompt Design and Engineering: Introduction and Advanced Methods
   Xavier Amatriain (2024)
   Introduces core concepts and advanced techniques in prompt design, including Chain-of-Thought and Reflection-based prompting.

4. A Prompt Pattern Catalog to Enhance Prompt Engineering with ChatGPT
   Jules White et al. (2023)
   A pattern-based approach to prompt engineering, offering reusable solutions to common problems when interacting with LLMs.

5. A Systematic Survey of Prompt Engineering on Vision-Language Foundation Models
   Jindong Gu et al. (2023)
   A deep dive into prompting techniques for multimodal models, summarizing their applications, challenges, and future research directions.

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These references serve as valuable resources for understanding different prompt engineering techniques and their potential applications.