title: RoMath: A Mathematical Reasoning Benchmark in Romanian
summary: Mathematics has long been conveyed through natural language, primarily for
  human understanding. With the rise of mechanized mathematics and proof
  assistants, there is a growing need to understand informal mathematical text,
  yet most existing benchmarks focus solely on English, overlooking other
  languages. This paper introduces RoMath, a Romanian mathematical reasoning
  benchmark suite comprising three datasets: RoMath-Baccalaureate,
  RoMath-Competitions and RoMath-Synthetic, which cover a range of mathematical
  domains and difficulty levels, aiming to improve non-English language models
  and promote multilingual AI development. By focusing on Romanian, a
  low-resource language with unique linguistic features, RoMath addresses the
  limitations of Anglo-centric models and emphasizes the need for dedicated
  resources beyond simple automatic translation. We benchmark several open-weight
  language models, highlighting the importance of creating resources for
  underrepresented languages. We make the code and dataset available.
paper_authors._id: 66ead57361228b02f8144cdf
paper_authors.name: Adrian Cosma
paper_authors._id: 66ead57361228b02f8144ce0
paper_authors.name: Ana-Maria Bucur
paper_authors._id: 66ead57361228b02f8144ce1
paper_authors.name: Emilian Radoi
paper_title: RoMath: A Mathematical Reasoning Benchmark in Romanian
paper_summary: Mathematics has long been conveyed through natural language, primarily for
  human understanding. With the rise of mechanized mathematics and proof
  assistants, there is a growing need to understand informal mathematical text,
  yet most existing benchmarks focus solely on English, overlooking other
  languages. This paper introduces RoMath, a Romanian mathematical reasoning
  benchmark suite comprising three datasets: RoMath-Baccalaureate,
  RoMath-Competitions and RoMath-Synthetic, which cover a range of mathematical
  domains and difficulty levels, aiming to improve non-English language models
  and promote multilingual AI development. By focusing on Romanian, a
  low-resource language with unique linguistic features, RoMath addresses the
  limitations of Anglo-centric models and emphasizes the need for dedicated
  resources beyond simple automatic translation. We benchmark several open-weight
  language models, highlighting the importance of creating resources for
  underrepresented languages. We make the code and dataset available.
paper_ai_keywords: benchmark suite datasets mathematical reasoning benchmark benchmark low-resource language linguistic features open-weight language models multilingual AI automated mathematics proof assistants informal mathematical text code dataset synthetic baccalaureate competitions mathematical domains difficulty levels automatic translation