Developing Corpus-based Translation Methods between Informal and Formal Mathematics: Project Description
Not on the map. Why?
Abstract (arXiv)
The goal of this project is to (i) accumulate annotated informal/formal mathematical corpora suitable for training semi-automated translation between informal and formal mathematics by statistical machine-translation methods, (ii) to develop such methods oriented at the formalization task, and in particular (iii) to combine such methods with learning-assisted automated reasoning that will serve as a strong semantic component. We describe these ideas, the initial set of corpora, and some initial experiments done over them.
Key facts. Cited by 7 papers in the map (data through 7 Oct 2026). First posted on arXiv 14 May 2014.
Builds on
No reference list yet.
Built on by
Citing papers per year: 2021: 1; 2022: 0; 2023: 1; 2024: 3; 2025: 1; 2026: 1.
7 papers.
- 2024A Survey on Deep Learning for Theorem Provingcited by 55
- 2024FormalAlign: Automated Alignment Evaluation for Autoformalizationcited by 19
- 2024Learning Guided Automated Reasoning: A Brief Surveycited by 7
- 2025Towards a Common Framework for Autoformalizationcited by 7
- 2021Disambiguating Symbolic Expressions in Informal Documentscited by 1
- 2026Munkres' General Topology Autoformalized in Isabelle/HOLcited by 1
- 2023Translating SUMO-K to Higher-Order Set Theorycited by 0
- 2026Munkres' General Topology Autoformalized in Isabelle/HOL8 Apr 2026
- 2025Towards a Common Framework for Autoformalization11 Sep 2025
- 2024FormalAlign: Automated Alignment Evaluation for Autoformalization14 Oct 2024
- 2024A Survey on Deep Learning for Theorem Proving15 Apr 2024
- 2024Learning Guided Automated Reasoning: A Brief Survey6 Mar 2024
- 2023Translating SUMO-K to Higher-Order Set Theory13 May 2023
- 2021Disambiguating Symbolic Expressions in Informal Documents25 Jan 2021