A_Prompt_Pattern_Catalog_to_Enhance_Prompt_Engineering_with_ChatGPT (1).pdf- “Enhancing Prompt Engineering: A Catalog of Techniques for ChatGPT” – “Improving LLM Conversations: A Pattern-Based Approach to Prompt Engineering” – “Optimizing Output Generation with Prompt Patterns for LLMs” – “Unlocking the Power of Prompt Engineering: Lessons Learned and Best Practices” – “Customizing LLM Interactions: A Framework for Effective Prompt Design” – “Combining Prompt Patterns for Enhanced Output Quality in LLM Conversations”

– Paper focuses on prompt engineering techniques for conversing with LLMs.
– Describes a catalog of prompt patterns to solve common problems.
– Provides a framework for documenting patterns and improving LLM outputs.
– Explains how prompts can be built from multiple patterns.

– The paper discusses the use of LLMs, specifically ChatGPT.
– Prompt engineering techniques are applied to converse effectively with LLMs.
– The paper provides a catalog of prompt patterns to improve LLM outputs.
– Prompt patterns can be combined to enhance the effectiveness of prompts.
– The prompt patterns capture naming, intent, motivation, and sample code.
– It is better to inject specific requirements into the prompt.
– The Flipped Interaction pattern allows for open-ended prompts.
– Specific prompts with constraints and information yield better outcomes.
– Experimentation may be needed to optimize the phrasing and flow of questions.

– Framework for documenting and applying prompt patterns for LLMs.
– Prompt patterns enrich capabilities of conversational LLMs.
– Prompt patterns can be combined to create larger and more complex capabilities.
– More work can be done to refine and expand prompt patterns.
– Prompt patterns can be used in innovative ways with LLMs.

– Paper presents a catalog of prompt engineering techniques for ChatGPT.
– Prompt patterns are reusable solutions to common problems in LLM conversations.
– Framework for documenting prompt patterns and adapting them to different domains.
– Catalog of patterns successfully improves the outputs of LLM conversations.
– Explains how prompts can be built from multiple patterns for better results.

– Framework for documenting and applying prompt patterns for LLMs.
– Prompt patterns enrich capabilities of conversational LLMs.
– More work needed to refine and expand prompt patterns.

– Provides a framework for documenting prompt engineering patterns.
– Presents a catalog of patterns to improve outputs of LLM conversations.
– Explains how prompts can be built from multiple patterns.

– Prompt engineering is a way to talk to language models effectively.
– Prompts are instructions given to models to get desired outputs.
– Prompt patterns are reusable solutions to common problems in prompt engineering.
– The paper provides a catalog of prompt patterns for different domains.
– Prompt patterns can be combined to create more effective prompts.