Enhancing Supervised Learning with Contrastive Markings in Neural Machine Translation Training

Supervised learning in Neural Machine Translation (NMT) typically follows a teacher forcing paradigm where reference tokens constitute the conditioning context in the model's prediction, instead of its own previous predictions. In order to alleviate this lack of exploration in the space of tran...

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Veröffentlicht in:	arXiv.org 2023-07
Hauptverfasser:	Berger, Nathaniel, Exel, Miriam, Huck, Matthias, Riezler, Stefan
Format:	Artikel
Sprache:	eng
Schlagworte:	Error correction Human error Hypotheses Machine translation Maximum likelihood estimation Supervised learning Training
Online-Zugang:	Volltext
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