Natural-Language to SysMLv2 Translation via Conformance-Driven Iterative Refinement

Jul 17, 2026

Researchers introduce a framework that translates natural-language descriptions into SysMLv2 models suitable for use in industrial modeling environments. The system employs a conformance checker within a generate-check-repair loop, ensuring that generated models achieve production-level acceptance. In evaluation on 151 prompts, the approach achieved 100% production conformance, compared to 51.16% for single-shot generation.

Why it matters: This work enables engineers to reliably generate deployable SysMLv2 artifacts directly from natural language, bridging the gap between informal requirements and formal system models.

Full story at: arXiv Software Engineering ↗