LLMON: An LLM-Native Markup Language, now in Granite 4.1 3B and 8B

Background and Motivation

Large language models rely heavily on context to generate tokens, but traditional formats like JSON were designed for parsers rather than causal models. Because transformers struggle with long spans and statistical quotation matching, models can become brittle or vulnerable to attacks such as prompt injections. To fix this, developers created LLMON (LLM Object Notation), which uses an XML-like structure with reserved special tokens to cleanly separate instructions, data, and requirements.

Implementation and Capabilities

Today, experimental preview models derived from Granite 4.1 base models, specifically granite-4.1-3b-LLMON-preview and granite-4.1-8b-LLMON-preview, have been released alongside a GitHub toolkit. Unlike regular chat templates that flatten inputs into a single string, LLMON wraps semantically coherent components in meaningful tags and uses an execution block to bind specific instructions to their exact data payloads. Evaluated on the OPI benchmark, these models virtually eliminate static indirect prompt injections, showing significantly higher robustness compared to standard open-source and closed-source models while matching general capabilities.