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An interpretable machine learning framework for classifying human and machine translations across genres

Neural modeling and large language models (LLMs) has led to a significant improvement in the quality of machine translation (MT) output. While MT increasingly rivals human output, “translationese”—systematic linguistic fingerprints left by the translation process—has long been studied qualitatively,...

Whakaahuatanga katoa

I tiakina i:
Ngā taipitopito rārangi puna kōrero
Ngā kaituhi matua: Lingxi Fan, Hongyang Du, Gan Huang
Hōputu: Artigo
Reo:Inglês
I whakaputaina: Frontiers Media S.A. 2026-06-01
Rangatū:Frontiers in Artificial Intelligence
Ngā marau:
Urunga tuihono:https://www.frontiersin.org/articles/10.3389/frai.2026.1813227/full
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