Building Multilingual Bridges: Data Mixing as the Pillar of Generalization for In-Language Reasoning
Reasoning language models have made substantial advances on a variety of complex tasks, yet their capabilities remain overwhelmingly English-centric: models primarily reason in English regardless of the language they are prompted in. This is inaccessible for non-English-speaking users, risks losing the intent of the original question, and forgoes knowledge more readily expressed in the target language. In this work, we advance L2 reasoning, the ability of a model to reason consistently in the language of the user's prompt, thus building an in-language bridge between the prompt and the answer. We approach this problem from a data-centric angle, investigating how to optimize data compositio...
| Authors | Mehrnaz Mofakhami, Ananya Sahu, Alejandro R. Salamanca et al. |
|---|---|
| Primary category | cs.CL |
| Published | 9 September 2026 |
| Last updated at source | 9 September 2026 |
Connected in the knowledge graph
- CohereLabs/tiny-aya-l2-thinkerModel · cited by
- CohereLabs/tiny-aya-l2-thinker-multilingual-reasoningDataset · cited by
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