AeroReq2LTL automates LTL generation from industrial aerospace requirements via LLMs with a data dictionary and templates, achieving 85% precision and 88% recall on real data.
Bridging Natural Language and Formal Specification–Automated Trans- lation of Software Requirements to LTL via Hierarchical Semantics Decomposition Using LLMs
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Pith papers citing it
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cs.SE 3years
2026 3verdicts
UNVERDICTED 3representative citing papers
An agentic LLM pipeline extracts and translates unstructured requirements into syntactically and semantically aligned formal properties, achieving 77.8% accuracy across three scenarios.
A prototype framework collects legal requirements and translates them into machine-actionable policies for federated data processing networks via policy-as-code and LLMs.
citing papers explorer
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Automated LTL Specification Generation from Industrial Aerospace Requirements
AeroReq2LTL automates LTL generation from industrial aerospace requirements via LLMs with a data dictionary and templates, achieving 85% precision and 88% recall on real data.
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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.
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Compliance Management for Federated Data Processing
A prototype framework collects legal requirements and translates them into machine-actionable policies for federated data processing networks via policy-as-code and LLMs.