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MMA: multilingual formal-to-informal training data

Contribution grade

Mathematical autoformalization data · Human-designed research method or resource

Reference score75,000Provisional editorial estimate of this exact contribution; its grade is assessed separately.

What changed

Generated natural-language informalizations of Lean4 and Isabelle statements to build a large paired corpus, then finetuned and compared multilingual-formal-language autoformalizers.

Scientific scope

Generated natural-language informalizations of Lean4 and Isabelle statements to build a large paired corpus, then finetuned and compared multilingual-formal-language autoformalizers. Multilingual here includes multiple formal languages, not guaranteed all human languages. Reverse-generated descriptions may be inaccurate; reported acceptable-with-minimal-correction outputs are not all exact verified translations. Inherits backtranslation and human formal libraries.

Evidence

The linked original sources describe the stated contribution and its evidence limits. WRS has not independently rerun the experiments or certified a proof. Multilingual here includes multiple formal languages, not guaranteed all human languages. Reverse-generated descriptions may be inaccurate; reported acceptable-with-minimal-correction outputs are not all exact verified translations. Inherits backtranslation and human formal libraries.

Contributors

Provisional WRS assessment, edition 2026-10-16.1. Independent expert calibration is pending. This grade does not certify correctness or assign ownership.

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