Large language models (LLMs) have achieved reasonable quality improvements in
machine translation (MT). However, most current research on MT-LLMs still faces significant …

Applying differential privacy (DP) by means of the DP-SGD algorithm to protect individual
data points during training is becoming increasingly popular in NLP. However, the choice of …

Despite the fact that context is known to be vital for resolving a range of translation
ambiguities, most traditional machine translation systems continue to be trained and to …

In this paper, we investigate the role of attention heads in Context-aware Machine
Translation models for pronoun disambiguation in the English-to-German and English-to …

Despite the strong research interest in document-level Machine Translation (MT), the test
sets dedicated to this task are still scarce. The existing test sets mainly cover topics from the …

Fine-tuning large language models (LLMs) for machine translation has shown
improvements in overall translation quality. However, it is unclear what is the impact of fine …

The question of context in neural machine translation often focuses on topics related to
document-level translation or intersentential context. However, there is a wide range of other …