ProofWala: A Framework for Multilingual Proof Data Synthesis and Theorem-Proving
📰 ArXiv cs.AI
Learn how ProofWala enables multilingual proof data synthesis and theorem-proving for neural approaches, and apply its framework to your own theorem-proving projects
Action Steps
- Build a proof engineering framework using ProofWala's architecture to interface with interactive theorem provers (ITPs)
- Extract structured proof data from ITPs using ProofWala's extraction tools
- Execute proof search at scale using ProofWala's parallel experimentation capabilities
- Configure ProofWala to support multilingual proof data synthesis
- Test ProofWala's framework on a repository-scale analysis to evaluate its performance
Who Needs to Know This
Researchers and developers working on neural theorem-proving and formal verification can benefit from ProofWala's framework for scalable and parallel proof search
Key Insight
💡 ProofWala provides a robust infrastructure for neural theorem-proving, enabling scalable and parallel proof search across multiple languages
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📚💻 ProofWala: A framework for multilingual proof data synthesis and theorem-proving. Scale up your neural theorem-proving with ProofWala! #AI #TheoremProving
Key Takeaways
Learn how ProofWala enables multilingual proof data synthesis and theorem-proving for neural approaches, and apply its framework to your own theorem-proving projects
Full Article
Title: ProofWala: A Framework for Multilingual Proof Data Synthesis and Theorem-Proving
Abstract:
arXiv:2502.04671v3 Announce Type: replace Abstract: 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 \tex
Abstract:
arXiv:2502.04671v3 Announce Type: replace Abstract: 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 \tex
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