An agentic LLM pipeline extracts and translates unstructured requirements into syntactically and semantically aligned formal properties, achieving 77.8% accuracy across three scenarios.
NL2CTL: automatic generation of formal requirements specifica- tions via large language models
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Towards an Agentic LLM-based Approach to Requirement Formalization from Unstructured Specifications
An agentic LLM pipeline extracts and translates unstructured requirements into syntactically and semantically aligned formal properties, achieving 77.8% accuracy across three scenarios.