ReasonXL: A Large-Scale Corpus for Language-Specific Reasoning in LLMs
Despite advances in multilingual capabilities, most large language models (LLMs) remain English-centric in their training and, crucially, in the reasoning traces they produce: even for non-English problems, they predominantly reason in English, leaving non-English users with intermediate reasoning they cannot follow. We address this disparity with two contributions. **(a)** We introduce $\texttt{ReasonXL}$, the first large-scale parallel corpus of cross-domain reasoning traces in five European languages (English, German, French, Italian, and Spanish): over 2.5M aligned samples (11B tokens) per language, each comprising prompt, reasoning trace, and final output, enabling direct supervision...
| Authors | Daniil Gurgurov, Tom Röhr, Sebastian von Rohrscheidt et al. |
|---|---|
| Primary category | cs.CL |
| Published | 14 April 2026 |
| Last updated at source | 10 October 2026 |
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