mlsanityData to 14 Oct 2026

A Survey in Mathematical Language Processing

arXiv 2205.15231 ↗First posted 30 May 2022cs.CLcited by 9

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Abstract (arXiv)

Informal mathematical text underpins real-world quantitative reasoning and communication. Developing sophisticated methods of retrieval and abstraction from this dual modality is crucial in the pursuit of the vision of automating discovery in quantitative science and mathematics. We track the development of informal mathematical language processing approaches across five strategic sub-areas in recent years, highlighting the prevailing successful methodological elements along with existing limitations.

Key facts. Cited by 9 papers in the map (data through 14 Oct 2026). Builds on 53 of its 150 references that are in the map. First posted on arXiv 30 May 2022.

Builds on

53 of 150 references.

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Cited by year

Citing papers per year: 2022: 1; 2023: 2; 2024: 4; 2025: 2.

9 papers.

  1. 2023LeanDojo: Theorem Proving with Retrieval-Augmented Language Modelscited by 427
  2. 2022A Survey of Deep Learning for Mathematical Reasoningcited by 124
  3. 2025A Survey on Large Language Models for Mathematical Reasoningcited by 52
  4. 2024CoMAT: Chain of Mathematically Annotated Thought Improves Mathematical Reasoningcited by 16
  5. 2024From Large Language Models and Optimization to Decision Optimization CoPilot: A Research Manifestocited by 11
  6. 2024STEM-POM: Evaluating Language Models Math-Symbol Reasoning in Document Parsingcited by 3
  7. 2023JiuZhang 2.0: A Unified Chinese Pre-trained Language Model for Multi-task Mathematical Problem Solvingcited by 2
  8. 2025E-Gen: Leveraging E-Graphs to Improve Continuous Representations of Symbolic Expressionscited by 1
  9. 2024SAAS: Solving Ability Amplification Strategy for Enhanced Mathematical Reasoning in Large Language Modelscited by 0