English(EN) Quantifying the Impact of Translation Errors on Multilingual LLM Evaluation

研究量化翻译错误对多语言大模型评估的影响

作者 PulseAugur 编辑部 · [1 个来源] · 2026-05-26 04:00

一篇新的研究论文探讨了翻译错误对多语言大型语言模型评估的影响。研究发现，机器翻译基准中的错误会显著影响大模型的性能，导致准确率可衡量的下降。研究人员开发了量化这些翻译错误的方法，并将其与人工标注进行比较，突显了对当前多语言大模型评估可靠性的担忧。 AI

影响强调了多语言大模型基准测试中潜在的不准确性，敦促采用更稳健的评估方法。

排序理由这是一篇发表在arXiv上的关于大模型评估的研究论文。[lever_c_demoted from research: ic=1 ai=1.0]

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arXiv cs.CL TIER_1 English(EN) · Klaudia-Doris Thellmann, Bernhard Stadler, Michael F\"arber, Jens Lehmann · 2026-05-26 04:00

量化翻译错误对多语言大模型评估的影响

arXiv:2605.24904v1 Announce Type: new Abstract: Machine-translated benchmarks are widely used to assess the multilingual capabilities of large language models (LLMs), yet translation errors in these benchmarks remain underexplored, raising concerns about the reliability and compa…