New SMT-based algorithm learns weighted automata efficiently

Researchers have developed a new SMT-based active learning algorithm for nondeterministic weighted automata (WFAs). This method offers a practical and robust alternative to existing techniques, producing minimal WFAs and demonstrating strong performance in experimental evaluations. The algorithm is parametric and guaranteed to produce minimal WFAs if it terminates, with a proven termination condition for finite semirings. AI

影响 Introduces a novel algorithm for learning weighted automata, potentially improving efficiency and size of learned models in formal language processing tasks.

排序理由 The cluster contains a new academic paper detailing a novel algorithm. [lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.LG 阅读 →

• Hankel
• weighted automata
• SMT

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