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.
English, Chase Walker, Dominic Simon, Sumit K
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VeriTrans achieves 94.46% SAT/UNSAT correctness on SatBench via LLM translation gated by round-trip similarity and deterministic neuro-symbolic execution.
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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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VeriTrans: Fine-Tuned LLM-Assisted NL-to-PL Translation via a Deterministic Neuro-Symbolic Pipeline
VeriTrans achieves 94.46% SAT/UNSAT correctness on SatBench via LLM translation gated by round-trip similarity and deterministic neuro-symbolic execution.