Acquiring new knowledge without forgetting what has been learned in a
se...
Previous works mostly focus on either multilingual or multi-domain aspec...
Transformer-based language models (TLMs) provide state-of-the-art perfor...
Neural Machine Translation (NMT) models are strong enough to convey sema...
Pivot-based neural machine translation (NMT) is commonly used in low-res...
Complex natural language applications such as speech translation or pivo...
This paper illustrates our approach to the shared task on large-scale
mu...
Context-aware neural machine translation (NMT) is a promising direction ...
We present effective pre-training strategies for neural machine translat...
Back-translation - data augmentation by translating target monolingual d...
In this paper, we empirically investigate applying word-level weights to...
We propose a novel model architecture and training algorithm to learn
bi...
We empirically investigate learning from partial feedback in neural mach...
We present the first real-world application of methods for improving neu...
In this paper, we introduce a hybrid search for attention-based neural
m...
In this paper, we discuss different methods which use meta information a...
We experiment graph-based Semi-Supervised Learning (SSL) of Conditional
...
Neural Machine Translation (NMT) is a new approach for Machine Translati...
In this paper, we propose an effective way for biasing the attention
mec...