A Survey of Languages for Formalizing Mathematics
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Abstract (arXiv)
In order to work with mathematical content in computer systems, it is necessary to represent it in formal languages. Ideally, these are supported by tools that verify the correctness of the content, allow computing with it, and produce human-readable documents. These goals are challenging to combine and state-of-the-art tools typically have to make difficult compromises. In this paper we discuss languages that have been created for this purpose, including logical languages of proof assistants and other formal systems, semi-formal languages, intermediate languages for exchanging mathematical knowledge, and language frameworks that allow building customized languages. We evaluate their advantages based on our experience in designing and applying languages and tools for formalizing mathematics. We reach the conclusion that no existing language is truly good enough yet and derive ideas for possible future improvements.
Key facts. Cited by 4 papers in the map (data through 13 Oct 2026). First posted on arXiv 26 May 2020.
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Citing papers per year: 2021: 1; 2022: 0; 2023: 1; 2024: 0; 2025: 1; 2026: 1.
4 papers.
- 2025Autoformalization in the Wild: Assessing LLMs on Real-World Mathematical Definitionscited by 20
- 2021Disambiguating Symbolic Expressions in Informal Documentscited by 1
- 2026MechMath: Sorrifier-Driven Formal Decomposition Workflow for Automated Theorem Provingcited by 1
- 2023OntoMathPRO 2.0 Ontology: Updates of the Formal Modelcited by 0
- 2026MechMath: Sorrifier-Driven Formal Decomposition Workflow for Automated Theorem Proving25 Mar 2026
- 2025Autoformalization in the Wild: Assessing LLMs on Real-World Mathematical Definitions17 Feb 2025
- 2023OntoMathPRO 2.0 Ontology: Updates of the Formal Model17 Mar 2023
- 2021Disambiguating Symbolic Expressions in Informal Documents25 Jan 2021