Papers by Keita Kurabe
Languages Still Left Behind: Toward a Better Multilingual Machine Translation Benchmark (2025.emnlp-main)
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Chihiro Taguchi, Seng Mai, Keita Kurabe, Yusuke Sakai, Georgina Agyei, Soudabeh Eslami, David Chiang
| Challenge: | Multilingual machine translation (MT) benchmarks are widely used to evaluate the capabilities of modern MT systems. |
| Approach: | They propose to use a multilingual machine translation benchmark to assess the capabilities of modern machine translation systems. |
| Outcome: | The FLORES+ benchmark claims to maintain a translation quality score of over 90% . however, the data in four languages falls short of the 90% quality standard . |