AI RESEARCH
ProofWala: A Framework for Multilingual Proof Data Synthesis and Theorem-Proving
arXiv CS.AI
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ArXi:2502.04671v3 Announce Type: replace Neural approaches to theorem proving require robust infrastructure for interfacing with interactive theorem provers (ITPs), extracting structured proof data, and executing proof search at scale. However, existing tooling is often assistant-specific and oriented toward file-level execution, making repository-scale analysis and parallel experimentation challenging. We present ProofWala, a multilingual proof engineering framework built around \texttt{itp-interface}, a reusable library for programmatic interaction with ITPs.