LLMON: An LLM-native Markup Language to Leverage Structure and Semantics at the LLM Interface

1. 1Define the structure and semantics of the input data using LLMON markup language
2. 2Use LLMON to distinguish between instructions and data in prompts
3. 3Pass the marked-up input to the LLM to leverage its structured and semantic understanding
4. 4Evaluate the performance of the LLM with LLMON markup language and refine its usage as needed

AI engineers and researchers working with LLMs can benefit from LLMON as it provides a more structured and semantic way of interacting with LLMs, enabling more effective and efficient use of these models

💡 LLMON enables more effective and efficient use of LLMs by providing a structured and semantic way of interacting with them

🚀 Introducing LLMON, a markup language for LLMs to leverage structure and semantics!