mlsanityData to 7 Oct 2026

mAceReason-Math: A Dataset of High-Quality Multilingual Math Problems Ready For RLVR

arXiv 2603.10767 ↗First posted 11 Mar 2026cs.CLcited by 2

On the map: LLM reasoning → Reinforcement learning for reasoning

Abstract (arXiv)

Reinforcement Learning with Verifiable Rewards (RLVR) has been successfully applied to significantly boost the capabilities of pretrained large language models, especially in the math and logic problem domains. However, current research and available training datasets remain English-centric. While multilingual training data and benchmarks have been created in the past, they were not created with RLVR and current model capability in mind, and their level of difficulty is often too low to provide appropriate training signals for current models. To address this gap, we provide mAceReason-Math, a dataset of high-quality translations of challenging math problems sourced from a corpus specifically curated for RLVR (AceReason-Math). We further take specific care to clean and improve our translations, resulting in a coverage of 14 languages with more than 10,000 samples per language. We release the dataset to facilitate multilingual RLVR research and benchmarking in the research community.

Key facts. Cited by 2 papers in the map (data through 7 Oct 2026). Placed in Reinforcement learning for reasoning, one of 17 directions in LLM reasoning. Builds on 6 of its 13 references that are in the map. First posted on arXiv 11 Mar 2026.

Builds on

6 of 13 references.

Closest ancestors · 3

Same direction, newest first

  1. 2025AceReason-Nemotron: Advancing Math and Code Reasoning through Reinforcement Learning22 May
  2. 2025DAPO: An Open-Source LLM Reinforcement Learning System at Scale18 Mar
  3. 2024Tulu 3: Pushing Frontiers in Open Language Model Post-Training22 Nov

Other references · 3

  1. 2021Training Verifiers to Solve Math Word Problemscited by 9,743
  2. 2025PolyMath: Evaluating Mathematical Reasoning in Multilingual Contextscited by 52
  3. 2025MMATH: A Multilingual Benchmark for Mathematical Reasoningcited by 16

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2026: 2.

2 papers.

  1. 2026Translate-R1: Cost-Aware Translation Tool Use via Reinforcement Learningcited by 0
  2. 2026Ring-Zero: Scaling Zero RL to a Trillion Parameters for Emergent Reasoningcited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2025Reinforcement Learning for Reasoning in Large Language Models with One Training Example
  2. 2026Multilingual Verifier Bias in RLVR: Benchmark, Rollout Diagnosis, and the Cross-Lingual Selection Bottleneck
  3. 2025Big-Math: A Large-Scale, High-Quality Math Dataset for Reinforcement Learning in Language Models
  4. 2026Learning from Less: Measuring the Effectiveness of RLVR in Low Data and Compute Regimes
  5. 2025Extending RLVR to Open-Ended Tasks via Verifiable Multiple-Choice Reformulation
  6. 2025Studying the Korean Word-Chain Game with RLVR: Mitigating Reward Conflicts via Curriculum Learning
  7. 2026To Mix or To Merge: Toward Multi-Domain Reinforcement Learning for Large Language Models
  8. 2025MATH-Beyond: A Benchmark for RL to Expand Beyond the Base Model