Apples to Apples? Towards Comparable Crosslingual Language Model Evaluation
Crosslingual evaluation of language models that enables fair comparisons remains a fundamental challenge in multilingual NLP. Existing studies adopt a variety of downstream tasks and intrinsic metrics with different theoretical justifications, yet there has been little empirical investigation into whether these approaches yield meaningful crosslingual conclusions. We systematically examine crosslingual evaluation approaches using controlled monolingual language models trained on parallel data with varying tokenizer vocabulary sizes and model sizes, and further validate our findings on multilingual LLMs. We further discuss challenges in achieving comparable downstream evaluation across lan...
| Authors | Xiulin Yang, Ethan Gotlieb Wilcox, Catherine Arnett |
|---|---|
| Primary category | cs.CL |
| Published | 25 August 2026 |
| Last updated at source | 30 August 2026 |
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