English(EN) Dialects of Translationese Shape Language Model Learning

来自不同源的翻译腔影响英语语言模型学习

作者 PulseAugur 编辑部 · [1 个来源] · 2026-08-25 04:00

一篇新的研究论文探讨了机器翻译文本（即翻译腔）如何影响小型英语语言模型的学习过程。该研究使用从24种不同源语言翻译而来的英语文本来训练模型，以分析源语言和翻译质量对语言可接受性和领域特定语言建模的影响。研究结果表明，词汇多样性会影响一般困惑度，而与英语的类型学相似性则显著影响语法表现，翻译质量是整体语言建模成功的有力预测指标。 AI

影响揭示了翻译数据的质量和来源如何影响大型语言模型（LLM）的性能，这对于多语言自然语言处理（NLP）应用至关重要。

排序理由在arXiv上发表的研究论文，详细介绍了关于语言模型学习的发现。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.CL 阅读 →

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arXiv cs.CL TIER_1 English(EN) · Jenny Kunz · 2026-08-25 04:00

翻译腔调塑造语言模型学习

arXiv:2602.16469v2 Announce Type: replace Abstract: Machine-translated data is widely used in multilingual NLP, particularly where native text is scarce. However, translated text differs systematically from native text. This phenomenon is known as translationese, and it reflects …

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翻译腔调塑造语言模型学习

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