Search Results for author: Miriam Exel

Found 6 papers, 1 papers with code

Terminology-Constrained Neural Machine Translation at SAP

no code implementations EAMT 2020 Miriam Exel, Bianka Buschbeck, Lauritz Brandt, Simona Doneva

This paper examines approaches to bias a neural machine translation model to adhere to terminology constraints in an industrial setup.

Machine Translation Translation

Contextual Refinement of Translations: Large Language Models for Sentence and Document-Level Post-Editing

no code implementations23 Oct 2023 Sai Koneru, Miriam Exel, Matthias Huck, Jan Niehues

Building on the LLM's exceptional ability to process and generate lengthy sequences, we also propose extending our approach to document-level translation.

Machine Translation NMT +2

Enhancing Supervised Learning with Contrastive Markings in Neural Machine Translation Training

no code implementations17 Jul 2023 Nathaniel Berger, Miriam Exel, Matthias Huck, Stefan Riezler

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.

Machine Translation NMT +1

A Parallel Evaluation Data Set of Software Documentation with Document Structure Annotation

1 code implementation AACL (WAT) 2020 Bianka Buschbeck, Miriam Exel

This paper accompanies the software documentation data set for machine translation, a parallel evaluation data set of data originating from the SAP Help Portal, that we released to the machine translation community for research purposes.

Machine Translation Translation

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