2 citations · 5 across the 8 of their papers we have counts for
8 papers · 1 filter
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…
Is Encoder-Decoder Redundant for Neural Machine Translation?
Yingbo Gao, Christian Herold, Zijian Yang +1
Encoder-decoder architecture is widely adopted for sequence-to-sequence modeling tasks. For machine translation, despite the evolution from long short-term memory networks to Trans…
Revisiting Checkpoint Averaging for Neural Machine Translation
Yingbo Gao, Christian Herold, Zijian Yang +1
Checkpoint averaging is a simple and effective method to boost the performance of converged neural machine translation models. The calculation is cheap to perform and the fact that…
Diving Deep into Context-Aware Neural Machine Translation
Jingjing Huo, Christian Herold, Yingbo Gao +3
Context-aware neural machine translation (NMT) is a promising direction to improve the translation quality by making use of the additional context, e.g., document-level translation…
Exploring Kernel Functions in the Softmax Layer for Contextual Word Classification
Yingbo Gao, Christian Herold, Weiyue Wang +1
Prominently used in support vector machines and logistic regressions, kernel functions (kernels) can implicitly map data points into high dimensional spaces and make it easier to l…