5 papers
IKUN for WMT24 General MT Task: LLMs Are here for Multilingual Machine Translation
Baohao Liao, Christian Herold, Shahram Khadivi +1
This paper introduces two multilingual systems, IKUN and IKUN-C, developed for the general machine translation task in WMT24. IKUN and IKUN-C represent an open system and a constra…
Document-Level Language Models for Machine Translation
Frithjof Petrick, Christian Herold, Pavel Petrushkov +2
Despite the known limitations, most machine translation systems today still operate on the sentence-level. One reason for this is, that most parallel training data is only sentence…
Improving Long Context Document-Level Machine Translation
Christian Herold, Hermann Ney
Document-level context for neural machine translation (NMT) is crucial to improve the translation consistency and cohesion, the translation of ambiguous inputs, as well as several…
On Search Strategies for Document-Level Neural Machine Translation
Christian Herold, Hermann Ney
Compared to sentence-level systems, document-level neural machine translation (NMT) models produce a more consistent output across a document and are able to better resolve ambigui…
Improving Language Model Integration for Neural Machine Translation
Christian Herold, Yingbo Gao, Mohammad Zeineldeen +1
The integration of language models for neural machine translation has been extensively studied in the past. It has been shown that an external language model, trained on additional…