cs.AI updates on arXiv.org 10月01日
中欧语言机器生成文本检测研究
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本文首次提出针对中欧语言机器生成文本检测的基准,并对比训练语言组合以确定最佳性能。研究聚焦多领域、多生成器和多语言评估,揭示检测方法各方面差异及对抗鲁棒性,发现监督微调检测器在中欧语言表现最佳。

arXiv:2509.26051v1 Announce Type: cross Abstract: Machine-generated text detection, as an important task, is predominantly focused on English in research. This makes the existing detectors almost unusable for non-English languages, relying purely on cross-lingual transferability. There exist only a few works focused on any of Central European languages, leaving the transferability towards these languages rather unexplored. We fill this gap by providing the first benchmark of detection methods focused on this region, while also providing comparison of train-languages combinations to identify the best performing ones. We focus on multi-domain, multi-generator, and multilingual evaluation, pinpointing the differences of individual aspects, as well as adversarial robustness of detection methods. Supervised finetuned detectors in the Central European languages are found the most performant in these languages as well as the most resistant against obfuscation.

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机器生成文本检测 中欧语言 多语言评估 对抗鲁棒性 监督微调
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