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![AINativeF Avatar](https://lunarcrush.com/gi/w:24/cr:twitter::1795402815298486272.png) AI Native Foundation [@AINativeF](/creator/twitter/AINativeF) on x 2177 followers
Created: 2025-07-25 03:00:16 UTC

XX. Promptomatix: An Automatic Prompt Optimization Framework for Large Language Models

🔑 Keywords: Large Language Models, prompt engineering, Promptomatix, automatic prompt optimization, AI Systems and Tools

💡 Category: Natural Language Processing

🌟 Research Objective:
   - To introduce Promptomatix, an automatic framework for optimizing prompts in large language models without manual effort or domain expertise.

🛠️ Research Methods:
   - Utilization of a meta-prompt-based optimizer and a DSPy-powered compiler within a modular framework that supports future extensions.
   - Analysis of user intent, generation of synthetic training data, selection of prompting strategies, and refinement of prompts using cost-aware objectives.

💬 Research Conclusions:
   - Promptomatix delivers competitive or superior performance across five task categories compared to existing libraries, while also reducing prompt length and computational overhead.

👉 Paper link:

![](https://pbs.twimg.com/media/Gwq-RFwWsAAXxPP.jpg)

XX engagements

![Engagements Line Chart](https://lunarcrush.com/gi/w:600/p:tweet::1948579023384084657/c:line.svg)

**Related Topics**
[coins ai](/topic/coins-ai)

[Post Link](https://x.com/AINativeF/status/1948579023384084657)

[GUEST ACCESS MODE: Data is scrambled or limited to provide examples. Make requests using your API key to unlock full data. Check https://lunarcrush.ai/auth for authentication information.]

AINativeF Avatar AI Native Foundation @AINativeF on x 2177 followers Created: 2025-07-25 03:00:16 UTC

XX. Promptomatix: An Automatic Prompt Optimization Framework for Large Language Models

🔑 Keywords: Large Language Models, prompt engineering, Promptomatix, automatic prompt optimization, AI Systems and Tools

💡 Category: Natural Language Processing

🌟 Research Objective:

  • To introduce Promptomatix, an automatic framework for optimizing prompts in large language models without manual effort or domain expertise.

🛠️ Research Methods:

  • Utilization of a meta-prompt-based optimizer and a DSPy-powered compiler within a modular framework that supports future extensions.
  • Analysis of user intent, generation of synthetic training data, selection of prompting strategies, and refinement of prompts using cost-aware objectives.

💬 Research Conclusions:

  • Promptomatix delivers competitive or superior performance across five task categories compared to existing libraries, while also reducing prompt length and computational overhead.

👉 Paper link:

XX engagements

Engagements Line Chart

Related Topics coins ai

Post Link

post/tweet::1948579023384084657
/post/tweet::1948579023384084657