Prompting Large Language Models with Human Error Markings for Self-Correcting Machine Translation

While large language models (LLMs) pre-trained on massive amounts of unpaired language data have reached the state-of-the-art in machine translation (MT) of general domain texts, post-editing (PE) is still required to correct errors and to enhance term translation quality in specialized domains. In...

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Veröffentlicht in:	arXiv.org 2024-06
Hauptverfasser:	Berger, Nathaniel, Riezler, Stefan, Exel, Miriam, Huck, Matthias
Format:	Artikel
Sprache:	eng
Schlagworte:	Error correction Human error Large language models Machine translation Translations
Online-Zugang:	Volltext
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