arXiv:2606.26525v1 Announce Type: new Abstract: Auto-formalization is critical for scalable formal verification, but existing progress largely focuses on isolated statements, while theory-scale auto-formalization, which coherently translates hundreds of interdependent definitions, lemmas, and theorems, remains open due to challenges in consistency, faithfulness, scalability, and correctness. In this paper, we introduce LCS-Bench, a stand-alone, theory-scale benchmark based on Logics for Computer Science. LCS-Bench is built through a novel semi-automated agentic pipeline that leverages concept
The increasing complexity and scale of AI systems necessitate more rigorous verification methods, driving demand for automated formalization tools.
This work directly addresses a critical barrier to scalable formal verification, which is essential for ensuring the reliability and safety of advanced AI and software systems.
The introduction of LCS-Bench and its pipeline could significantly advance the field of auto-formalization from isolated statements to theory-scale systems.
- · Formal verification software developers
- · AI safety researchers
- · High-assurance software industries
- · Organizations developing complex AI systems
- · Manual formal verification processes
- · Projects lacking robust verification protocols
Improved reliability and reduced bug rates in complex software and AI models.
Accelerated development and deployment of mission-critical AI applications due to heightened trust in their correctness.
A potential reduction in the economic and human costs associated with software errors and AI failures, leading to safer autonomous systems.
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Read at arXiv cs.LG