4 citations · 5 across the 4 of their papers we have counts for
5 papers · 1 filter
Deploying a BERT-based Query-Title Relevance Classifier in a Production System: a View from the Trenches
Leonard Dahlmann, Tomer Lancewicki
The Bidirectional Encoder Representations from Transformers (BERT) model has been radically improving the performance of many Natural Language Processing (NLP) tasks such as Text C…
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…
Word-based Domain Adaptation for Neural Machine Translation
Shen Yan, Leonard Dahlmann, Pavel Petrushkov +2
In this paper, we empirically investigate applying word-level weights to adapt neural machine translation to e-commerce domains, where small e-commerce datasets and large out-of-do…
Neural Machine Translation Leveraging Phrase-based Models in a Hybrid Search
Leonard Dahlmann, Evgeny Matusov, Pavel Petrushkov +1
In this paper, we introduce a hybrid search for attention-based neural machine translation (NMT). A target phrase learned with statistical MT models extends a hypothesis in the NMT…
Neural and Statistical Methods for Leveraging Meta-information in Machine Translation
Shahram Khadivi, Patrick Wilken, Leonard Dahlmann +1
In this paper, we discuss different methods which use meta information and richer context that may accompany source language input to improve machine translation quality. We focus…