Multilingual Reasoning Gym: Multilingual Scaling of Procedural Reasoning Environments
Konstantin Dobler, Simon Lehnerer, Federico Scozzafava, Jonathan Janke, Mohamed Ali

TL;DR
The paper introduces the Multilingual Reasoning Gym, a tool for generating verifiable reasoning problems across 14 languages, facilitating scalable multilingual reasoning research with procedural generation and parallel data creation.
Contribution
It extends Reasoning Gym to support 14 languages with verifiable, procedurally generated problems, enabling scalable multilingual reasoning research and evaluation.
Findings
Supports 14 languages with native-speaker validated templates
Enables large-scale crosslingual data generation
Maintains core benefits of procedural problem generation
Abstract
We present the Multilingual Reasoning Gym, an extension of Reasoning Gym (Stojanovski et al., 2025), that procedurally generates verifiable reasoning problems across 14 languages. We translate templates for 94 tasks with native-speaker validation in 10 languages and targeted code or template adaptations to ensure linguistic naturalness. The Multilingual Reasoning Gym preserves the core benefits of the procedural generation approach used in the original Reasoning Gym, such as virtually unlimited problem instance generation and adjustable difficulty, and remains directly usable for Reinforcement Learning from Verifiable Rewards and evaluation settings. Problems in the Multilingual Reasoning Gym are parallel across languages, enabling crosslingually parallel data generation at massive scale due to the procedural nature of the environments. We release our implementation to support research…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsNatural Language Processing Techniques · Topic Modeling · Multimodal Machine Learning Applications
