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English(EN) Cultivar: A Contrastive and Locale-Oriented Translation Benchmark for Investigating Contamination and Localisation Robustness

新的Cultivar基准探测翻译模型的数据污染和地区偏见

研究人员推出了Cultivar,这是一个新的基准,旨在评估多语言翻译模型在数据污染和本地化鲁棒性方面的表现。与传统的从英语翻译的基准不同,Cultivar使用源对比方法,并结合了FLORES数据集的特定地区子集。这种方法可以检测数据污染,并评估模型在不同文化和地区语言变体中的表现。对32个开源模型的基准测试显示,专门的翻译模型鲁棒性较差,一些模型可能过度拟合FLORES数据集,并且模型在源自美国的内​​容上的表现通常优于其他地区。 AI

影响 该基准有望带来更鲁棒、更具文化意识的翻译模型,从而提高在不同语言社区中的表现。

排序理由 该集群描述了一个用于评估机器翻译模型的新学术基准。

在 Hugging Face Daily Papers 阅读 →

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新的Cultivar基准探测翻译模型的数据污染和地区偏见

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该集群描述了一个用于评估机器翻译模型的新学术基准。
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报道来源 [2]

  1. arXiv cs.AI TIER_1 English(EN) · Pinzhen Chen, Koel Dutta Chowdhury, Xiaoya Xu, David Tan, Doreen Osmelak, Ona de Gibert, Ariun-Erdene Tumurchuluun, Ashok Urlana, Fedor Sizov, Hale Sirin, Jesujoba Alabi, Karrar Talib Abed, Mateusz Klimaszewski, Nikolay Bogoychev, Niyati Bafna, Patricia … ·

    Cultivar:一个对比性和面向本地化的翻译基准,用于研究污染和本地化鲁棒性

    arXiv:2608.09766v1 Announce Type: cross Abstract: Multilingual translation benchmarks are typically sourced in English and translated into other languages, treating language pairs as the unit of evaluation---a design that is prone to contamination over time and overlooks locale a…

  2. Hugging Face Daily Papers TIER_1 English(EN) ·

    Cultivar:一个对比性和面向本地化的翻译基准,用于研究污染和本地化鲁棒性

    Researchers propose source-contrastive evaluation via a localized benchmark to detect data contamination and assess localization robustness in multilingual translation models.